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Oral
Wed Jul 11 02:00 AM -- 02:20 AM (PDT) @ A1
Problem Dependent Reinforcement Learning Bounds Which Can Identify Bandit Structure in MDPs
In Reinforcement Learning 1
Andrea Zanette · Emma Brunskill
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:00 AM -- 02:20 AM (PDT) @ Victoria
DiCE: The Infinitely Differentiable Monte Carlo Estimator
In Deep Learning (Neural Network Architectures) 1
Jakob Foerster · Gregory Farquhar · Maruan Al-Shedivat · Tim Rocktäschel · Eric Xing · Shimon Whiteson
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:00 AM -- 02:20 AM (PDT) @ A3
Transfer Learning via Learning to Transfer
In Transfer and Multi-Task Learning 1
Ying WEI · Yu Zhang · Junzhou Huang · Qiang Yang
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:00 AM -- 02:20 AM (PDT) @ A6
Nonparametric Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information
In Statistical Learning Theory 1
Yichong Xu · Hariank Muthakana · Sivaraman Balakrishnan · Aarti Singh · Artur Dubrawski
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:00 AM -- 02:20 AM (PDT) @ A5
Predict and Constrain: Modeling Cardinality in Deep Structured Prediction
In Structured Prediction 1
Nataly Brukhim · Amir Globerson
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:00 AM -- 02:20 AM (PDT) @ A9
Optimal Tuning for Divide-and-conquer Kernel Ridge Regression with Massive Data
In Parallel and Distributed Learning 1
Ganggang Xu · Zuofeng Shang · Guang Cheng
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:00 AM -- 02:20 AM (PDT) @ K1 + K2
Learning to Explain: An Information-Theoretic Perspective on Model Interpretation
In Feature Selection 1
Jianbo Chen · Le Song · Martin Wainwright · Michael Jordan
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:00 AM -- 02:20 AM (PDT) @ A7
Learning Continuous Hierarchies in the Lorentz Model of Hyperbolic Geometry
In Representation Learning 1
Maximilian Nickel · Douwe Kiela
[ PDF] 
Oral
Wed Jul 11 02:00 AM -- 02:20 AM (PDT) @ A4
Crowdsourcing with Arbitrary Adversaries
In Unsupervised Learning 1
Matthäus Kleindessner · Pranjal Awasthi
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:00 AM -- 02:20 AM (PDT) @ K11
Equivalence of Multicategory SVM and Simplex Cone SVM: Fast Computations and Statistical Theory
In Clustering 1
Guillaume Pouliot
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:20 AM -- 02:30 AM (PDT) @ K1 + K2
Nonoverlap-Promoting Variable Selection
In Feature Selection 1
Pengtao Xie · Hongbao Zhang · Yichen Zhu · Eric Xing
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:20 AM -- 02:40 AM (PDT) @ A3
Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory
In Transfer and Multi-Task Learning 1
Ron Amit · Ron Meir
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:20 AM -- 02:30 AM (PDT) @ K11
Quickshift++: Provably Good Initializations for Sample-Based Mean Shift
In Clustering 1
Heinrich Jiang · Jennifer Jang · Samory Kpotufe
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:20 AM -- 02:40 AM (PDT) @ A5
SparseMAP: Differentiable Sparse Structured Inference
In Structured Prediction 1
Vlad Niculae · Andre Filipe Torres Martins · Mathieu Blondel · Claire Cardie
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:20 AM -- 02:30 AM (PDT) @ A4
Analysis of Minimax Error Rate for Crowdsourcing and Its Application to Worker Clustering Model
In Unsupervised Learning 1
Hideaki Imamura · Issei Sato · Masashi Sugiyama
[ PDF] 
Oral
Wed Jul 11 02:20 AM -- 02:30 AM (PDT) @ A1
Learning with Abandonment
In Reinforcement Learning 1
Sven Schmit · Ramesh Johari
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:20 AM -- 02:30 AM (PDT) @ A9
Distributed Nonparametric Regression under Communication Constraints
In Parallel and Distributed Learning 1
Yuancheng Zhu · John Lafferty
[ PDF] 
Oral
Wed Jul 11 02:20 AM -- 02:30 AM (PDT) @ Victoria
Learning to search with MCTSnets
In Deep Learning (Neural Network Architectures) 1
Arthur Guez · Theophane Weber · Ioannis Antonoglou · Karen Simonyan · Oriol Vinyals · Daan Wierstra · Remi Munos · David Silver
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:20 AM -- 02:30 AM (PDT) @ A7
Hyperbolic Entailment Cones for Learning Hierarchical Embeddings
In Representation Learning 1
Octavian-Eugen Ganea · Gary Becigneul · Thomas Hofmann
[ PDF] 
Oral
Wed Jul 11 02:20 AM -- 02:30 AM (PDT) @ A6
Do Outliers Ruin Collaboration?
In Statistical Learning Theory 1
Mingda Qiao
[ PDF] 
Oral
Wed Jul 11 02:30 AM -- 02:40 AM (PDT) @ A9
Coded Sparse Matrix Multiplication
In Parallel and Distributed Learning 1
Sinong Wang · Jiashang Liu · Ness Shroff
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:30 AM -- 02:40 AM (PDT) @ A1
Lipschitz Continuity in Model-based Reinforcement Learning
In Reinforcement Learning 1
Kavosh Asadi · Dipendra Misra · Michael L. Littman
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:30 AM -- 02:40 AM (PDT) @ K1 + K2
MSplit LBI: Realizing Feature Selection and Dense Estimation Simultaneously in Few-shot and Zero-shot Learning
In Feature Selection 1
Bo Zhao · Xinwei Sun · Yanwei Fu · Yuan Yao · Yizhou Wang
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:30 AM -- 02:40 AM (PDT) @ A7
Tree Edit Distance Learning via Adaptive Symbol Embeddings
In Representation Learning 1
Benjamin Paaßen · Claudio Gallicchio · Alessio Micheli · CITEC Barbara Hammer
[ PDF] 
Oral
Wed Jul 11 02:30 AM -- 02:40 AM (PDT) @ A4
Conditional Noise-Contrastive Estimation of Unnormalised Models
In Unsupervised Learning 1
Ciwan Ceylan · Michael Gutmann
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:30 AM -- 02:40 AM (PDT) @ A6
LeapsAndBounds: A Method for Approximately Optimal Algorithm Configuration
In Statistical Learning Theory 1
Gellért Weisz · András György · Csaba Szepesvari
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:30 AM -- 02:40 AM (PDT) @ K11
Hierarchical Clustering with Structural Constraints
In Clustering 1
Evangelos Chatziafratis · Rad Niazadeh · Moses Charikar
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:30 AM -- 02:40 AM (PDT) @ Victoria
Differentiable plasticity: training plastic neural networks with backpropagation
In Deep Learning (Neural Network Architectures) 1
Thomas Miconi · Kenneth Stanley · Jeff Clune
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:40 AM -- 02:50 AM (PDT) @ A9
Towards More Efficient Stochastic Decentralized Learning: Faster Convergence and Sparse Communication
In Parallel and Distributed Learning 1
Zebang Shen · Aryan Mokhtari · Tengfei Zhou · Peilin Zhao · Hui Qian
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:40 AM -- 02:50 AM (PDT) @ A4
Deep One-Class Classification
In Unsupervised Learning 1
Lukas Ruff · Nico Görnitz · Lucas Deecke · Shoaib Ahmed Siddiqui · Robert Vandermeulen · Alexander Binder · Emmanuel Müller · Marius Kloft
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:40 AM -- 02:50 AM (PDT) @ K11
K-means clustering using random matrix sparsification
In Clustering 1
Kaushik Sinha
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:40 AM -- 02:50 AM (PDT) @ Victoria
TACO: Learning Task Decomposition via Temporal Alignment for Control
In Deep Learning (Neural Network Architectures) 1
Kyriacos Shiarlis · Markus Wulfmeier · Sasha Salter · Shimon Whiteson · Ingmar Posner
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:40 AM -- 02:50 AM (PDT) @ A7
Learning K-way D-dimensional Discrete Codes for Compact Embedding Representations
In Representation Learning 1
Ting Chen · Martin Min · Yizhou Sun
[ PDF] 
Oral
Wed Jul 11 02:40 AM -- 02:50 AM (PDT) @ A6
Variational Network Inference: Strong and Stable with Concrete Support
In Statistical Learning Theory 1
Amir Dezfouli · Edwin Bonilla · Richard Nock
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:40 AM -- 02:50 AM (PDT) @ A1
Implicit Quantile Networks for Distributional Reinforcement Learning
In Reinforcement Learning 1
Will Dabney · Georg Ostrovski · David Silver · Remi Munos
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:40 AM -- 02:50 AM (PDT) @ A3
Bilevel Programming for Hyperparameter Optimization and Meta-Learning
In Transfer and Multi-Task Learning 1
Luca Franceschi · Paolo Frasconi · Saverio Salzo · Riccardo Grazzi · Massimiliano Pontil
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:40 AM -- 02:50 AM (PDT) @ A5
Efficient and Consistent Adversarial Bipartite Matching
In Structured Prediction 1
Rizal Fathony · Sima Behpour · Xinhua Zhang · Brian Ziebart
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:40 AM -- 02:50 AM (PDT) @ K1 + K2
Black Box FDR
In Feature Selection 1
Wesley Tansey · Yixin Wang · David Blei · Raul Rabadan
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:50 AM -- 03:00 AM (PDT) @ Victoria
Graph Networks as Learnable Physics Engines for Inference and Control
In Deep Learning (Neural Network Architectures) 1
Alvaro Sanchez-Gonzalez · Nicolas Heess · Jost Springenberg · Josh Merel · Martin Riedmiller · Raia Hadsell · Peter Battaglia
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:50 AM -- 03:00 AM (PDT) @ K1 + K2
Variable Selection via Penalized Neural Network: a Drop-Out-One Loss Approach
In Feature Selection 1
Mao Ye · Yan Sun
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:50 AM -- 03:00 AM (PDT) @ A3
Pseudo-task Augmentation: From Deep Multitask Learning to Intratask Sharing—and Back
In Transfer and Multi-Task Learning 1
Elliot Meyerson · Risto Miikkulainen
[ PDF] 
Oral
Wed Jul 11 02:50 AM -- 03:00 AM (PDT) @ A4
Deep Density Destructors
In Unsupervised Learning 1
David Inouye · Pradeep Ravikumar
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:50 AM -- 03:00 AM (PDT) @ A7
CoVeR: Learning Covariate-Specific Vector Representations with Tensor Decompositions
In Representation Learning 1
Kevin Tian · Teng Zhang · James Zou
[ PDF] 
Oral
Wed Jul 11 02:50 AM -- 03:00 AM (PDT) @ A5
Learning to Speed Up Structured Output Prediction
In Structured Prediction 1
Xingyuan Pan · Vivek Srikumar
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:50 AM -- 03:00 AM (PDT) @ A9
Faster Derivative-Free Stochastic Algorithm for Shared Memory Machines
In Parallel and Distributed Learning 1
Bin Gu · Zhouyuan Huo · Cheng Deng · Heng Huang
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:50 AM -- 03:00 AM (PDT) @ A6
Network Global Testing by Counting Graphlets
In Statistical Learning Theory 1
Jiashun Jin · Zheng Ke · Shengming Luo
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:50 AM -- 03:00 AM (PDT) @ K11
Clustering Semi-Random Mixtures of Gaussians
In Clustering 1
Aravindan Vijayaraghavan · Pranjal Awasthi
[ PDF]  [ PDF]  [ Video] 
Oral
Wed Jul 11 02:50 AM -- 03:00 AM (PDT) @ A1
More Robust Doubly Robust Off-policy Evaluation
In Reinforcement Learning 1
Mehrdad Farajtabar · Yinlam Chow · Mohammad Ghavamzadeh
[ PDF]  [ Video] 
Oral
Wed Jul 11 04:30 AM -- 04:50 AM (PDT) @ A5
WHInter: A Working set algorithm for High-dimensional sparse second order Interaction models
In Sparsity and Compressed Sensing 1
Marine LE MORVAN · Jean-Philippe Vert
[ PDF]  [ Video] 
Oral
Wed Jul 11 04:30 AM -- 04:50 AM (PDT) @ A4
Markov Modulated Gaussian Cox Processes for Semi-Stationary Intensity Modeling of Events Data
In Gaussian Processes 1
Minyoung Kim
[ PDF]  [ Video] 
Oral
Wed Jul 11 04:30 AM -- 04:50 AM (PDT) @ Victoria
RadialGAN: Leveraging multiple datasets to improve target-specific predictive models using Generative Adversarial Networks
In Deep Learning (Neural Network Architectures) 2
Jinsung Yoon · James Jordon · Mihaela van der Schaar
[ PDF]  [ Video] 
Oral
Wed Jul 11 04:30 AM -- 04:50 AM (PDT) @ A3
Stagewise Safe Bayesian Optimization with Gaussian Processes
In Optimization (Bayesian) 1
Yanan Sui · Vincent Zhuang · Joel Burdick · Yisong Yue
[ PDF] 
Oral
Wed Jul 11 04:30 AM -- 04:50 AM (PDT) @ A7
Improving Optimization in Models With Continuous Symmetry Breaking
In Representation Learning 2
Robert Bamler · Stephan Mandt
[ PDF] 
Oral
Wed Jul 11 04:30 AM -- 04:50 AM (PDT) @ A9
Asynchronous Decentralized Parallel Stochastic Gradient Descent
In Optimization (Non-convex) 1
Xiangru Lian · Wei Zhang · Ce Zhang · Ji Liu
[ PDF]  [ Video] 
Oral
Wed Jul 11 04:30 AM -- 04:50 AM (PDT) @ A1
Coordinated Exploration in Concurrent Reinforcement Learning
In Reinforcement Learning 2
Maria Dimakopoulou · Benjamin Van Roy
[ PDF]  [ Video] 
Oral
Wed Jul 11 04:30 AM -- 04:50 AM (PDT) @ K1 + K2
Limits of Estimating Heterogeneous Treatment Effects: Guidelines for Practical Algorithm Design
In Other Applications 1
Ahmed M. Alaa · Mihaela van der Schaar
[ PDF]  [ Video] 
Oral
Wed Jul 11 04:30 AM -- 04:50 AM (PDT) @ A6
Data-Dependent Stability of Stochastic Gradient Descent
In Statistical Learning Theory 2
Ilja Kuzborskij · Christoph H. Lampert
[ PDF]  [ Video] 
Oral
Wed Jul 11 04:30 AM -- 04:50 AM (PDT) @ K11
Leveraging Well-Conditioned Bases: Streaming and Distributed Summaries in Minkowski $p$-Norms
In Dimensionality Reduction 1
Charlie Dickens · Graham Cormode · David Woodruff
[ PDF]  [ PDF]  [ Video] 
Oral
Wed Jul 11 04:50 AM -- 05:10 AM (PDT) @ A7
A probabilistic framework for multi-view feature learning with many-to-many associations via neural networks
In Representation Learning 2
Akifumi Okuno · Tetsuya Hada · Hidetoshi Shimodaira
[ PDF] 
Oral
Wed Jul 11 04:50 AM -- 05:10 AM (PDT) @ K1 + K2
Variance Regularized Counterfactual Risk Minimization via Variational Divergence Minimization
In Other Applications 1
Hang Wu · May Wang
[ PDF]  [ Video] 
Oral
Wed Jul 11 04:50 AM -- 05:10 AM (PDT) @ K11
Subspace Embedding and Linear Regression with Orlicz Norm
In Dimensionality Reduction 1
Alexandr Andoni · Chengyu Lin · Ying Sheng · Peilin Zhong · Ruiqi Zhong
[ PDF]  [ Video] 
Oral
Wed Jul 11 04:50 AM -- 05:00 AM (PDT) @ A1
Structured Evolution with Compact Architectures for Scalable Policy Optimization
In Reinforcement Learning 2
Krzysztof Choromanski · Mark Rowland · Vikas Sindhwani · Richard E Turner · Adrian Weller
[ PDF]  [ Video] 
Oral
Wed Jul 11 04:50 AM -- 05:10 AM (PDT) @ A6
Stability and Generalization of Learning Algorithms that Converge to Global Optima
In Statistical Learning Theory 2
Zachary Charles · Dimitris Papailiopoulos
[ PDF]  [ Video] 
Oral
Wed Jul 11 04:50 AM -- 05:10 AM (PDT) @ A4
Bayesian Quadrature for Multiple Related Integrals
In Gaussian Processes 1
Xiaoyue Xi · Francois-Xavier Briol · Mark Girolami
[ PDF]  [ Video] 
Oral
Wed Jul 11 04:50 AM -- 05:10 AM (PDT) @ A5
Nearly Optimal Robust Subspace Tracking
In Sparsity and Compressed Sensing 1
Praneeth Narayanamurthy · Namrata Vaswani
[ PDF]  [ Video] 
Oral
Wed Jul 11 04:50 AM -- 05:10 AM (PDT) @ Victoria
Semi-Supervised Learning via Compact Latent Space Clustering
In Deep Learning (Neural Network Architectures) 2
Konstantinos Kamnitsas · Daniel C. Castro · Loic Le Folgoc · Ian Walker · Ryutaro Tanno · Daniel Rueckert · Ben Glocker · Antonio Criminisi · Aditya Nori
[ PDF]  [ Video] 
Oral
Wed Jul 11 04:50 AM -- 05:10 AM (PDT) @ A3
BOCK : Bayesian Optimization with Cylindrical Kernels
In Optimization (Bayesian) 1
ChangYong Oh · Efstratios Gavves · Max Welling
[ PDF] 
Oral
Wed Jul 11 04:50 AM -- 05:10 AM (PDT) @ A9
signSGD: Compressed Optimisation for Non-Convex Problems
In Optimization (Non-convex) 1
Jeremy Bernstein · Yu-Xiang Wang · Kamyar Azizzadenesheli · Anima Anandkumar
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:00 AM -- 05:10 AM (PDT) @ A1
Spotlight: Optimizing Device Placement for Training Deep Neural Networks
In Reinforcement Learning 2
Yuanxiang Gao · Li Chen · Baochun Li
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:10 AM -- 05:20 AM (PDT) @ A5
Safe Element Screening for Submodular Function Minimization
In Sparsity and Compressed Sensing 1
Weizhong Zhang · Bin Hong · Lin Ma · Wei Liu · Tong Zhang
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:10 AM -- 05:20 AM (PDT) @ A4
Differentiable Compositional Kernel Learning for Gaussian Processes
In Gaussian Processes 1
Shengyang Sun · Guodong Zhang · Chaoqi Wang · Wenyuan Zeng · Jiaman Li · Roger Grosse
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:10 AM -- 05:20 AM (PDT) @ K11
Stochastic PCA with $\ell_2$ and $\ell_1$ Regularization
In Dimensionality Reduction 1
Poorya Mianjy · Raman Arora
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:10 AM -- 05:20 AM (PDT) @ Victoria
Conditional Neural Processes
In Deep Learning (Neural Network Architectures) 2
Marta Garnelo · Dan Rosenbaum · Chris Maddison · Tiago Ramalho · David Saxton · Murray Shanahan · Yee Teh · Danilo J. Rezende · S. M. Ali Eslami
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:10 AM -- 05:20 AM (PDT) @ K1 + K2
An Estimation and Analysis Framework for the Rasch Model
In Other Applications 1
Andrew Lan · Mung Chiang · Christoph Studer
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:10 AM -- 05:20 AM (PDT) @ A9
Katyusha X: Simple Momentum Method for Stochastic Sum-of-Nonconvex Optimization
In Optimization (Non-convex) 1
Zeyuan Allen-Zhu
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:10 AM -- 05:20 AM (PDT) @ A3
BOHB: Robust and Efficient Hyperparameter Optimization at Scale
In Optimization (Bayesian) 1
Stefan Falkner · Aaron Klein · Frank Hutter
[ PDF] 
Oral
Wed Jul 11 05:10 AM -- 05:20 AM (PDT) @ A1
Gated Path Planning Networks
In Reinforcement Learning 2
Lisa Lee · Emilio Parisotto · Devendra Singh Chaplot · Eric Xing · Ruslan Salakhutdinov
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:10 AM -- 05:20 AM (PDT) @ A6
Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces
In Statistical Learning Theory 2
Junhong Lin · Volkan Cevher
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:10 AM -- 05:20 AM (PDT) @ A7
Learning Steady-States of Iterative Algorithms over Graphs
In Representation Learning 2
Hanjun Dai · Zornitsa Kozareva · Bo Dai · Alex Smola · Le Song
[ PDF] 
Oral
Wed Jul 11 05:20 AM -- 05:30 AM (PDT) @ A7
Anonymous Walk Embeddings
In Representation Learning 2
Sergey Ivanov · Evgeny Burnaev
[ PDF] 
Oral
Wed Jul 11 05:20 AM -- 05:30 AM (PDT) @ K11
Streaming Principal Component Analysis in Noisy Setting
In Dimensionality Reduction 1
Teodor Vanislavov Marinov · Poorya Mianjy · Raman Arora
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:20 AM -- 05:30 AM (PDT) @ A4
Generalized Robust Bayesian Committee Machine for Large-scale Gaussian Process Regression
In Gaussian Processes 1
Haitao Liu · Jianfei Cai · Yi Wang · Yew Soon ONG
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:20 AM -- 05:30 AM (PDT) @ Victoria
A Semantic Loss Function for Deep Learning with Symbolic Knowledge
In Deep Learning (Neural Network Architectures) 2
Jingyi Xu · Zilu Zhang · Tal Friedman · Yitao Liang · Guy Van den Broeck
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:20 AM -- 05:30 AM (PDT) @ A9
$D^2$: Decentralized Training over Decentralized Data
In Optimization (Non-convex) 1
Hanlin Tang · Xiangru Lian · Ming Yan · Ce Zhang · Ji Liu
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:20 AM -- 05:30 AM (PDT) @ A5
Online Convolutional Sparse Coding with Sample-Dependent Dictionary
In Sparsity and Compressed Sensing 1
Yaqing WANG · Quanming Yao · James Kwok · Lionel NI
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:20 AM -- 05:30 AM (PDT) @ K1 + K2
End-to-end Active Object Tracking via Reinforcement Learning
In Other Applications 1
Wenhan Luo · Peng Sun · Fangwei Zhong · Wei Liu · Tong Zhang · Yizhou Wang
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:20 AM -- 05:30 AM (PDT) @ A1
Best Arm Identification in Linear Bandits with Linear Dimension Dependency
In Reinforcement Learning 2
Chao Tao · Saúl A. Blanco · Yuan Zhou
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:20 AM -- 05:30 AM (PDT) @ A6
Dropout Training, Data-dependent Regularization, and Generalization Bounds
In Statistical Learning Theory 2
Wenlong Mou · Yuchen Zhou · Jun Gao · Liwei Wang
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:20 AM -- 05:30 AM (PDT) @ A3
Bayesian Optimization of Combinatorial Structures
In Optimization (Bayesian) 1
Ricardo Baptista · Matthias Poloczek
[ PDF] 
Oral
Wed Jul 11 05:30 AM -- 05:50 AM (PDT) @ A7
Generative Temporal Models with Spatial Memory for Partially Observed Environments
In Representation Learning 3
Marco Fraccaro · Danilo J. Rezende · Yori Zwols · Alexander Pritzel · S. M. Ali Eslami · Fabio Viola
[ PDF] 
Oral
Wed Jul 11 05:30 AM -- 05:50 AM (PDT) @ A6
Information Theoretic Guarantees for Empirical Risk Minimization with Applications to Model Selection and Large-Scale Optimization
In Statistical Learning Theory 3
Ibrahim Alabdulmohsin
[ PDF] 
Oral
Wed Jul 11 05:30 AM -- 05:50 AM (PDT) @ A3
Design of Experiments for Model Discrimination Hybridising Analytical and Data-Driven Approaches
In Active Learning 1
Simon Olofsson · Marc P Deisenroth · Ruth Misener
[ PDF] 
Oral
Wed Jul 11 05:30 AM -- 05:50 AM (PDT) @ K1 + K2
Deep Predictive Coding Network for Object Recognition
In Computer Vision 1
Haiguang Wen · Kuan Han · Junxing Shi · Yizhen Zhang · Eugenio Culurciello · Zhongming Liu
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:30 AM -- 05:50 AM (PDT) @ A1
Structured Control Nets for Deep Reinforcement Learning
In Reinforcement Learning 3
Mario Srouji · Jian Zhang · Ruslan Salakhutdinov
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:30 AM -- 05:50 AM (PDT) @ Victoria
Non-linear motor control by local learning in spiking neural networks
In Deep Learning (Neural Network Architectures) 3
Aditya Gilra · Wulfram Gerstner
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:30 AM -- 05:50 AM (PDT) @ K11
Linear Spectral Estimators and an Application to Phase Retrieval
In Sparsity and Compressed Sensing 2
Ramina Ghods · Andrew Lan · Tom Goldstein · Christoph Studer
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:30 AM -- 05:50 AM (PDT) @ A9
An Alternative View: When Does SGD Escape Local Minima?
In Optimization (Non-convex) 2
Bobby Kleinberg · Yuanzhi Li · Yang Yuan
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:30 AM -- 05:50 AM (PDT) @ A4
Variational Inference and Model Selection with Generalized Evidence Bounds
In Deep Learning (Bayesian) 1
Liqun Chen · Chenyang Tao · RUIYI (ROY) ZHANG · Ricardo Henao · Lawrence Carin
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:30 AM -- 05:50 AM (PDT) @ A5
The Limits of Maxing, Ranking, and Preference Learning
In Ranking and Preference Learning 1
Moein Falahatgar · Ayush Jain · Alon Orlitsky · Venkatadheeraj Pichapati · Vaishakh Ravindrakumar
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:50 AM -- 06:10 AM (PDT) @ A9
Escaping Saddles with Stochastic Gradients
In Optimization (Non-convex) 2
Hadi Daneshmand · Jonas Kohler · Aurelien Lucchi · Thomas Hofmann
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:50 AM -- 06:10 AM (PDT) @ K11
Covariate Adjusted Precision Matrix Estimation via Nonconvex Optimization
In Sparsity and Compressed Sensing 2
Jinghui Chen · Pan Xu · Lingxiao Wang · Jian Ma · Quanquan Gu
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:50 AM -- 06:00 AM (PDT) @ A6
The Generalization Error of Dictionary Learning with Moreau Envelopes
In Statistical Learning Theory 3
ALEXANDROS GEORGOGIANNIS
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:50 AM -- 06:10 AM (PDT) @ A1
Latent Space Policies for Hierarchical Reinforcement Learning
In Reinforcement Learning 3
Tuomas Haarnoja · Kristian Hartikainen · Pieter Abbeel · Sergey Levine
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:50 AM -- 06:00 AM (PDT) @ A7
Disentangling by Factorising
In Representation Learning 3
Hyunjik Kim · Andriy Mnih
[ PDF] 
Oral
Wed Jul 11 05:50 AM -- 06:00 AM (PDT) @ K1 + K2
Gradually Updated Neural Networks for Large-Scale Image Recognition
In Computer Vision 1
Siyuan Qiao · Zhishuai Zhang · Wei Shen · Bo Wang · Alan Yuille
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:50 AM -- 06:10 AM (PDT) @ A3
Selecting Representative Examples for Program Synthesis
In Active Learning 1
Yewen Pu · Zachery Miranda · Armando Solar-Lezama · Leslie Kaelbling
[ PDF] 
Oral
Wed Jul 11 05:50 AM -- 06:00 AM (PDT) @ Victoria
PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning
In Deep Learning (Neural Network Architectures) 3
Yunbo Wang · Zhifeng Gao · Mingsheng Long · Jianmin Wang · Philip Yu
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:50 AM -- 06:00 AM (PDT) @ A5
Learning a Mixture of Two Multinomial Logits
In Ranking and Preference Learning 1
Flavio Chierichetti · Ravi Kumar · Andrew Tomkins
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:50 AM -- 06:10 AM (PDT) @ A4
Fixing a Broken ELBO
In Deep Learning (Bayesian) 1
Alexander Alemi · Ben Poole · Ian Fischer · Joshua V Dillon · Rif Saurous · Kevin Murphy
[ PDF]  [ Video] 
Oral
Wed Jul 11 06:00 AM -- 06:10 AM (PDT) @ A6
On Learning Sparsely Used Dictionaries from Incomplete Samples
In Statistical Learning Theory 3
Thanh Nguyen · Akshay Soni · Chinmay Hegde
[ PDF]  [ Video] 
Oral
Wed Jul 11 06:00 AM -- 06:10 AM (PDT) @ Victoria
Hierarchical Long-term Video Prediction without Supervision
In Deep Learning (Neural Network Architectures) 3
Nevan Wichers · Ruben Villegas · Dumitru Erhan · Honglak Lee
[ PDF]  [ Video] 
Oral
Wed Jul 11 06:00 AM -- 06:10 AM (PDT) @ A7
Discovering Interpretable Representations for Both Deep Generative and Discriminative Models
In Representation Learning 3
Tameem Adel · Zoubin Ghahramani · Adrian Weller
[ PDF] 
Oral
Wed Jul 11 06:00 AM -- 06:10 AM (PDT) @ A5
The Weighted Kendall and High-order Kernels for Permutations
In Ranking and Preference Learning 1
Yunlong Jiao · Jean-Philippe Vert
[ PDF]  [ Video] 
Oral
Wed Jul 11 06:00 AM -- 06:10 AM (PDT) @ K1 + K2
Neural Inverse Rendering for General Reflectance Photometric Stereo
In Computer Vision 1
Tatsunori Taniai · Takanori Maehara
[ PDF]  [ Video] 
Oral
Wed Jul 11 06:10 AM -- 06:20 AM (PDT) @ A9
Stochastic Variance-Reduced Cubic Regularized Newton Method
In Optimization (Non-convex) 2
Dongruo Zhou · Pan Xu · Quanquan Gu
[ PDF]  [ Video] 
Oral
Wed Jul 11 06:10 AM -- 06:20 AM (PDT) @ A7
Learning Independent Causal Mechanisms
In Representation Learning 3
Giambattista Parascandolo · Niki Kilbertus · Mateo Rojas-Carulla · Bernhard Schölkopf
[ PDF] 
Oral
Wed Jul 11 06:10 AM -- 06:20 AM (PDT) @ A6
The Well-Tempered Lasso
In Statistical Learning Theory 3
Yuanzhi Li · Yoram Singer
[ PDF]  [ Video] 
Oral
Wed Jul 11 06:10 AM -- 06:20 AM (PDT) @ K11
Signal and Noise Statistics Oblivious Orthogonal Matching Pursuit
In Sparsity and Compressed Sensing 2
Sreejith Kallummil · Sheetal Kalyani
[ PDF]  [ Video] 
Oral
Wed Jul 11 06:10 AM -- 06:20 AM (PDT) @ A1
Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings
In Reinforcement Learning 3
John Co-Reyes · Yu Xuan Liu · Abhishek Gupta · Benjamin Eysenbach · Pieter Abbeel · Sergey Levine
[ PDF]  [ Video] 
Oral
Wed Jul 11 06:10 AM -- 06:20 AM (PDT) @ Victoria
Exploiting the Potential of Standard Convolutional Autoencoders for Image Restoration by Evolutionary Search
In Deep Learning (Neural Network Architectures) 3
Masanori SUGANUMA · Mete Ozay · Takayuki Okatani
[ PDF]  [ Video] 
Oral
Wed Jul 11 06:10 AM -- 06:20 AM (PDT) @ K1 + K2
One-Shot Segmentation in Clutter
In Computer Vision 1
Claudio Michaelis · Matthias Bethge · Alexander Ecker
[ PDF]  [ Video] 
Oral
Wed Jul 11 06:10 AM -- 06:20 AM (PDT) @ A4
Tighter Variational Bounds are Not Necessarily Better
In Deep Learning (Bayesian) 1
Tom Rainforth · Adam Kosiorek · Tuan Anh Le · Chris Maddison · Maximilian Igl · Frank Wood · Yee-Whye Teh
[ PDF]  [ Video] 
Oral
Wed Jul 11 06:10 AM -- 06:20 AM (PDT) @ A3
On the Relationship between Data Efficiency and Error for Uncertainty Sampling
In Active Learning 1
Stephen Mussmann · Percy Liang
[ PDF] 
Oral
Wed Jul 11 06:10 AM -- 06:20 AM (PDT) @ A5
Parameterized Algorithms for the Matrix Completion Problem
In Ranking and Preference Learning 1
Robert Ganian · DePaul Iyad Kanj · Sebastian Ordyniak · Stefan Szeider
[ PDF]  [ Video] 
Oral
Wed Jul 11 06:20 AM -- 06:30 AM (PDT) @ A7
Contextual Graph Markov Model: A Deep and Generative Approach to Graph Processing
In Representation Learning 3
Davide Bacciu · Federico Errica · Alessio Micheli
[ PDF] 
Oral
Wed Jul 11 06:20 AM -- 06:30 AM (PDT) @ A6
Differentially Private Identity and Equivalence Testing of Discrete Distributions
In Statistical Learning Theory 3
Maryam Aliakbarpour · Ilias Diakonikolas · MIT Ronitt Rubinfeld
[ PDF]  [ Video] 
Oral
Wed Jul 11 06:20 AM -- 06:30 AM (PDT) @ A1
An Inference-Based Policy Gradient Method for Learning Options
In Reinforcement Learning 3
Matthew Smith · Herke van Hoof · Joelle Pineau
[ PDF]  [ Video] 
Oral
Wed Jul 11 06:20 AM -- 06:30 AM (PDT) @ Victoria
Model-Level Dual Learning
In Deep Learning (Neural Network Architectures) 3
Yingce Xia · Xu Tan · Fei Tian · Tao Qin · Nenghai Yu · Tie-Yan Liu
[ PDF]  [ Video] 
Oral
Wed Jul 11 06:20 AM -- 06:30 AM (PDT) @ A9
Non-convex Conditional Gradient Sliding
In Optimization (Non-convex) 2
chao qu · Yan Li · Huan Xu
[ PDF]  [ Video] 
Oral
Wed Jul 11 06:20 AM -- 06:30 AM (PDT) @ K1 + K2
Active Testing: An Efficient and Robust Framework for Estimating Accuracy
In Computer Vision 1
Phuc Nguyen · Deva Ramanan · Charless Fowlkes
[ PDF]  [ Video] 
Oral
Wed Jul 11 06:20 AM -- 06:30 AM (PDT) @ K11
Testing Sparsity over Known and Unknown Bases
In Sparsity and Compressed Sensing 2
Siddharth Barman · Arnab Bhattacharyya · Suprovat Ghoshal
[ PDF]  [ Video] 
Oral
Wed Jul 11 06:20 AM -- 06:30 AM (PDT) @ A4
Continuous-Time Flows for Efficient Inference and Density Estimation
In Deep Learning (Bayesian) 1
Changyou Chen · Chunyuan Li · Liquan Chen · Wenlin Wang · Yunchen Pu · Lawrence Carin
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:00 AM -- 07:20 AM (PDT) @ A3
Competitive Multi-agent Inverse Reinforcement Learning with Sub-optimal Demonstrations
In Reinforcement Learning 5
IEMS Xingyu Wang · Diego Klabjan
[ PDF] 
Oral
Wed Jul 11 07:00 AM -- 07:20 AM (PDT) @ A6
Differentially Private Matrix Completion Revisited
In Privacy, Anonymity, and Security 1
Prateek Jain · Om Dipakbhai Thakkar · Abhradeep Thakurta
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:00 AM -- 07:20 AM (PDT) @ A1
Programmatically Interpretable Reinforcement Learning
In Reinforcement Learning 4
Abhinav Verma · Vijayaraghavan Murali · Rishabh Singh · Pushmeet Kohli · Swarat Chaudhuri
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:00 AM -- 07:20 AM (PDT) @ A4
Semi-Implicit Variational Inference
In Approximate Inference 1
Mingzhang Yin · Mingyuan Zhou
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:00 AM -- 07:20 AM (PDT) @ A7
Which Training Methods for GANs do actually Converge?
In Generative Models 1
Lars Mescheder · Andreas Geiger · Sebastian Nowozin
[ PDF] 
Oral
Wed Jul 11 07:00 AM -- 07:20 AM (PDT) @ A5
Stochastic Training of Graph Convolutional Networks with Variance Reduction
In Networks and Relational Learning 1
Jianfei Chen · Jun Zhu · Le Song
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:00 AM -- 07:20 AM (PDT) @ K11
Weakly Submodular Maximization Beyond Cardinality Constraints: Does Randomization Help Greedy?
In Optimization (Combinatorial) 1
Lin Chen · Moran Feldman · Amin Karbasi
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:00 AM -- 07:20 AM (PDT) @ Victoria
Adafactor: Adaptive Learning Rates with Sublinear Memory Cost
In Deep Learning (Neural Network Architectures) 4
Noam Shazeer · Mitchell Stern
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:00 AM -- 07:20 AM (PDT) @ A9
Dissipativity Theory for Accelerating Stochastic Variance Reduction: A Unified Analysis of SVRG and Katyusha Using Semidefinite Programs
In Optimization (Convex) 1
Bin Hu · Stephen Wright · Laurent Lessard
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:00 AM -- 07:20 AM (PDT) @ K1 + K2
Dynamical Isometry and a Mean Field Theory of CNNs: How to Train 10,000-Layer Vanilla Convolutional Neural Networks
In Deep Learning (Theory) 1
Lechao Xiao · Yasaman Bahri · Jascha Sohl-Dickstein · Samuel Schoenholz · Jeffrey Pennington
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:20 AM -- 07:40 AM (PDT) @ A4
Efficient Gradient-Free Variational Inference using Policy Search
In Approximate Inference 1
Oleg Arenz · Gerhard Neumann · Mingjun Zhong
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:20 AM -- 07:40 AM (PDT) @ A7
Chi-square Generative Adversarial Network
In Generative Models 1
Chenyang Tao · Liqun Chen · Ricardo Henao · Jianfeng Feng · Lawrence Carin
[ PDF] 
Oral
Wed Jul 11 07:20 AM -- 07:40 AM (PDT) @ A5
Representation Learning on Graphs with Jumping Knowledge Networks
In Networks and Relational Learning 1
Keyulu Xu · Chengtao Li · Yonglong Tian · Tomohiro Sonobe · Ken-ichi Kawarabayashi · Stefanie Jegelka
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:20 AM -- 07:30 AM (PDT) @ Victoria
Orthogonal Recurrent Neural Networks with Scaled Cayley Transform
In Deep Learning (Neural Network Architectures) 4
Kyle Helfrich · Devin Willmott · Qiang Ye
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:20 AM -- 07:30 AM (PDT) @ A9
Lyapunov Functions for First-Order Methods: Tight Automated Convergence Guarantees
In Optimization (Convex) 1
Adrien Taylor · Bryan Van Scoy · Laurent Lessard
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:20 AM -- 07:30 AM (PDT) @ A6
Mitigating Bias in Adaptive Data Gathering via Differential Privacy
In Privacy, Anonymity, and Security 1
Seth Neel · Aaron Roth
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:20 AM -- 07:40 AM (PDT) @ A3
Feedback-Based Tree Search for Reinforcement Learning
In Reinforcement Learning 5
Daniel Jiang · Emmanuel Ekwedike · Han Liu
[ PDF] 
Oral
Wed Jul 11 07:20 AM -- 07:40 AM (PDT) @ K1 + K2
The Dynamics of Learning: A Random Matrix Approach
In Deep Learning (Theory) 1
Zhenyu Liao · Romain Couillet
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:20 AM -- 07:40 AM (PDT) @ K11
Beyond 1/2-Approximation for Submodular Maximization on Massive Data Streams
In Optimization (Combinatorial) 1
Ashkan Norouzi-Fard · Jakub Tarnawski · Slobodan Mitrovic · Amir Zandieh · Aidasadat Mousavifar · Ola Svensson
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:20 AM -- 07:40 AM (PDT) @ A1
Learning by Playing - Solving Sparse Reward Tasks from Scratch
In Reinforcement Learning 4
Martin Riedmiller · Roland Hafner · Thomas Lampe · Michael Neunert · Jonas Degrave · Tom Van de Wiele · Vlad Mnih · Nicolas Heess · Jost Springenberg
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:30 AM -- 07:40 AM (PDT) @ A9
ADMM and Accelerated ADMM as Continuous Dynamical Systems
In Optimization (Convex) 1
Guilherme Franca · Daniel Robinson · Rene Vidal
[ PDF] 
Oral
Wed Jul 11 07:30 AM -- 07:40 AM (PDT) @ Victoria
Kronecker Recurrent Units
In Deep Learning (Neural Network Architectures) 4
Cijo Jose · Mouhamadou Moustapha Cisse · Francois Fleuret
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:30 AM -- 07:40 AM (PDT) @ A6
Local Private Hypothesis Testing: Chi-Square Tests
In Privacy, Anonymity, and Security 1
Marco Gaboardi · Ryan Rogers
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:40 AM -- 07:50 AM (PDT) @ A3
Deep Reinforcement Learning in Continuous Action Spaces: a Case Study in the Game of Simulated Curling
In Reinforcement Learning 5
kyowoon Lee · Sol-A Kim · Jaesik Choi · Seong-Whan Lee
[ PDF] 
Oral
Wed Jul 11 07:40 AM -- 07:50 AM (PDT) @ A4
A Spectral Approach to Gradient Estimation for Implicit Distributions
In Approximate Inference 1
Jiaxin Shi · Shengyang Sun · Jun Zhu
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:40 AM -- 07:50 AM (PDT) @ K1 + K2
On the Optimization of Deep Networks: Implicit Acceleration by Overparameterization
In Deep Learning (Theory) 1
Sanjeev Arora · Nadav Cohen · Elad Hazan
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:40 AM -- 07:50 AM (PDT) @ A9
Computational Optimal Transport: Complexity by Accelerated Gradient Descent Is Better Than by Sinkhorn's Algorithm
In Optimization (Convex) 1
Pavel Dvurechenskii · Alexander Gasnikov · Alexey Kroshnin
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:40 AM -- 07:50 AM (PDT) @ Victoria
Fast Parametric Learning with Activation Memorization
In Deep Learning (Neural Network Architectures) 4
Jack Rae · Chris Dyer · Peter Dayan · Timothy Lillicrap
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:40 AM -- 07:50 AM (PDT) @ A5
Learning Diffusion using Hyperparameters
In Networks and Relational Learning 1
Dimitrios Kalimeris · Yaron Singer · Karthik Subbian · Udi Weinsberg
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:40 AM -- 07:50 AM (PDT) @ A1
Automatic Goal Generation for Reinforcement Learning Agents
In Reinforcement Learning 4
Carlos Florensa · David Held · Xinyang Geng · Pieter Abbeel
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:40 AM -- 07:50 AM (PDT) @ K11
Scalable Deletion-Robust Submodular Maximization: Data Summarization with Privacy and Fairness Constraints
In Optimization (Combinatorial) 1
Ehsan Kazemi · Morteza Zadimoghaddam · Amin Karbasi
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:40 AM -- 07:50 AM (PDT) @ A7
Learning Implicit Generative Models with the Method of Learned Moments
In Generative Models 1
Suman Ravuri · Shakir Mohamed · Mihaela Rosca · Oriol Vinyals
[ PDF] 
Oral
Wed Jul 11 07:40 AM -- 07:50 AM (PDT) @ A6
Locally Private Hypothesis Testing
In Privacy, Anonymity, and Security 1
Or Sheffet
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:50 AM -- 08:00 AM (PDT) @ A9
An Efficient Semismooth Newton based Algorithm for Convex Clustering
In Optimization (Convex) 1
Yancheng Yuan · Defeng Sun · Kim-Chuan Toh
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:50 AM -- 08:00 AM (PDT) @ A7
A Classification-Based Study of Covariate Shift in GAN Distributions
In Generative Models 1
Shibani Santurkar · Ludwig Schmidt · Aleksander Madry
[ PDF] 
Oral
Wed Jul 11 07:50 AM -- 08:00 AM (PDT) @ A6
INSPECTRE: Privately Estimating the Unseen
In Privacy, Anonymity, and Security 1
Jayadev Acharya · Gautam Kamath · Ziteng Sun · Huanyu Zhang
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:50 AM -- 08:00 AM (PDT) @ K1 + K2
Deep Linear Networks with Arbitrary Loss: All Local Minima Are Global
In Deep Learning (Theory) 1
Thomas Laurent · James von Brecht
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:50 AM -- 08:00 AM (PDT) @ K11
Data Summarization at Scale: A Two-Stage Submodular Approach
In Optimization (Combinatorial) 1
Marko Mitrovic · Ehsan Kazemi · Morteza Zadimoghaddam · Amin Karbasi
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:50 AM -- 08:00 AM (PDT) @ A4
Quasi-Monte Carlo Variational Inference
In Approximate Inference 1
Alexander Buchholz · Florian Wenzel · Stephan Mandt
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:50 AM -- 08:00 AM (PDT) @ A1
Universal Planning Networks: Learning Generalizable Representations for Visuomotor Control
In Reinforcement Learning 4
Aravind Srinivas · Allan Jabri · Pieter Abbeel · Sergey Levine · Chelsea Finn
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:50 AM -- 08:00 AM (PDT) @ A5
Canonical Tensor Decomposition for Knowledge Base Completion
In Networks and Relational Learning 1
Timothee Lacroix · Nicolas Usunier · Guillaume Obozinski
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:50 AM -- 08:00 AM (PDT) @ A3
Learning the Reward Function for a Misspecified Model
In Reinforcement Learning 5
Erik Talvitie
[ PDF] 
Oral
Wed Jul 11 07:50 AM -- 08:00 AM (PDT) @ Victoria
Dynamic Evaluation of Neural Sequence Models
In Deep Learning (Neural Network Architectures) 4
Ben Krause · Emmanuel Kahembwe · Iain Murray · Steve Renals
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:00 AM -- 08:20 AM (PDT) @ A4
Yes, but Did It Work?: Evaluating Variational Inference
In Approximate Inference 2
Yuling Yao · Aki Vehtari · Daniel Simpson · Andrew Gelman
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:00 AM -- 08:20 AM (PDT) @ A1
Efficient Bias-Span-Constrained Exploration-Exploitation in Reinforcement Learning
In Reinforcement Learning 6
Ronan Fruit · Matteo Pirotta · Alessandro Lazaric · Ronald Ortner
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:00 AM -- 08:20 AM (PDT) @ Victoria
Decoupled Parallel Backpropagation with Convergence Guarantee
In Deep Learning (Neural Network Architectures) 5
Zhouyuan Huo · Bin Gu · Qian Yang · Heng Huang
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:00 AM -- 08:20 AM (PDT) @ K11
Learning to Optimize Combinatorial Functions
In Optimization (Combinatorial) 2
Nir Rosenfeld · Eric Balkanski · Amir Globerson · Yaron Singer
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:00 AM -- 08:20 AM (PDT) @ A3
Machine Theory of Mind
In Reinforcement Learning 7
Neil Rabinowitz · Frank Perbet · Francis Song · Chiyuan Zhang · S. M. Ali Eslami · Matthew Botvinick
[ PDF] 
Oral
Wed Jul 11 08:00 AM -- 08:20 AM (PDT) @ A9
The Power of Interpolation: Understanding the Effectiveness of SGD in Modern Over-parametrized Learning
In Optimization (Convex) 2
Siyuan Ma · Raef Bassily · Mikhail Belkin
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:00 AM -- 08:20 AM (PDT) @ A7
Differentiable Abstract Interpretation for Provably Robust Neural Networks
In Deep Learning (Adversarial) 1
Matthew Mirman · Timon Gehr · Martin Vechev
[ PDF] 
Oral
Wed Jul 11 08:00 AM -- 08:20 AM (PDT) @ K1 + K2
Essentially No Barriers in Neural Network Energy Landscape
In Deep Learning (Theory) 2
Felix Draxler · Kambis Veschgini · Manfred Salmhofer · Fred Hamprecht
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:00 AM -- 08:20 AM (PDT) @ A6
Delayed Impact of Fair Machine Learning
In Society Impacts of Machine Learning 1
Lydia T. Liu · Sarah Dean · Esther Rolf · Max Simchowitz · Moritz Hardt
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:00 AM -- 08:20 AM (PDT) @ A5
Dependent Relational Gamma Process Models for Longitudinal Networks
In Networks and Relational Learning 2
Sikun Yang · Heinz Koeppl
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:20 AM -- 08:40 AM (PDT) @ A4
Augment and Reduce: Stochastic Inference for Large Categorical Distributions
In Approximate Inference 2
Francisco Ruiz · Michalis Titsias · Adji Bousso Dieng · David Blei
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:20 AM -- 08:40 AM (PDT) @ A6
Fairness Without Demographics in Repeated Loss Minimization
In Society Impacts of Machine Learning 1
Tatsunori Hashimoto · Megha Srivastava · Hongseok Namkoong · Percy Liang
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:20 AM -- 08:30 AM (PDT) @ A9
Fast Variance Reduction Method with Stochastic Batch Size
In Optimization (Convex) 2
University of California Xuanqing Liu · Cho-Jui Hsieh
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:20 AM -- 08:40 AM (PDT) @ Victoria
Efficient Neural Architecture Search via Parameters Sharing
In Deep Learning (Neural Network Architectures) 5
Hieu Pham · Melody Guan · Barret Zoph · Quoc Le · Jeff Dean
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:20 AM -- 08:30 AM (PDT) @ K1 + K2
Comparing Dynamics: Deep Neural Networks versus Glassy Systems
In Deep Learning (Theory) 2
Marco Baity-Jesi · Levent Sagun · Mario Geiger · Stefano Spigler · Gerard Arous · Chiara Cammarota · Yann LeCun · Matthieu Wyart · Giulio Biroli
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:20 AM -- 08:30 AM (PDT) @ K11
Proportional Allocation: Simple, Distributed, and Diverse Matching with High Entropy
In Optimization (Combinatorial) 2
Shipra Agarwal · Morteza Zadimoghaddam · Vahab Mirrokni
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:20 AM -- 08:40 AM (PDT) @ A1
Path Consistency Learning in Tsallis Entropy Regularized MDPs
In Reinforcement Learning 6
Yinlam Chow · Ofir Nachum · Mohammad Ghavamzadeh
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:20 AM -- 08:40 AM (PDT) @ A5
NetGAN: Generating Graphs via Random Walks
In Networks and Relational Learning 2
Aleksandar Bojchevski · Oleksandr Shchur · Daniel Zügner · Stephan Günnemann
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:20 AM -- 08:40 AM (PDT) @ A3
Transfer in Deep Reinforcement Learning Using Successor Features and Generalised Policy Improvement
In Reinforcement Learning 7
Andre Barreto · Diana Borsa · John Quan · Tom Schaul · David Silver · Matteo Hessel · Daniel J. Mankowitz · Augustin Zidek · Remi Munos
[ PDF] 
Oral
Wed Jul 11 08:20 AM -- 08:40 AM (PDT) @ A7
Provable Defenses against Adversarial Examples via the Convex Outer Adversarial Polytope
In Deep Learning (Adversarial) 1
Eric Wong · Zico Kolter
[ PDF] 
Oral
Wed Jul 11 08:30 AM -- 08:40 AM (PDT) @ K1 + K2
Not All Samples Are Created Equal: Deep Learning with Importance Sampling
In Deep Learning (Theory) 2
Angelos Katharopoulos · Francois Fleuret
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:30 AM -- 08:40 AM (PDT) @ K11
Binary Partitions with Approximate Minimum Impurity
In Optimization (Combinatorial) 2
Eduardo Laber · Marco Molinaro · Felipe de A. Mello Pereira
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:30 AM -- 08:40 AM (PDT) @ A9
SGD and Hogwild! Convergence Without the Bounded Gradients Assumption
In Optimization (Convex) 2
Lam Nguyen · PHUONG_HA NGUYEN · Marten van Dijk · Peter Richtarik · Katya Scheinberg · Martin Takac
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:40 AM -- 08:50 AM (PDT) @ A9
Lightweight Stochastic Optimization for Minimizing Finite Sums with Infinite Data
In Optimization (Convex) 2
Shuai Zheng · James Kwok
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:40 AM -- 08:50 AM (PDT) @ A5
GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models
In Networks and Relational Learning 2
Jiaxuan You · Rex (Zhitao) Ying · Xiang Ren · Will Hamilton · Jure Leskovec
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:40 AM -- 08:50 AM (PDT) @ K11
Partial Optimality and Fast Lower Bounds for Weighted Correlation Clustering
In Optimization (Combinatorial) 2
Jan-Hendrik Lange · Andreas Karrenbauer · Bjoern Andres
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:40 AM -- 08:50 AM (PDT) @ A6
Nonconvex Optimization for Regression with Fairness Constraints
In Society Impacts of Machine Learning 1
Junpei Komiyama · Akiko Takeda · Junya Honda · Hajime Shimao
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:40 AM -- 08:50 AM (PDT) @ Victoria
Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization
In Deep Learning (Neural Network Architectures) 5
Jiong Zhang · Qi Lei · Inderjit Dhillon
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:40 AM -- 08:50 AM (PDT) @ A4
Black-Box Variational Inference for Stochastic Differential Equations
In Approximate Inference 2
Tom Ryder · Andrew Golightly · Stephen McGough · Dennis Prangle
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:40 AM -- 08:50 AM (PDT) @ A3
Been There, Done That: Meta-Learning with Episodic Recall
In Reinforcement Learning 7
Samuel Ritter · Jane Wang · Zeb Kurth-Nelson · Siddhant Jayakumar · Charles Blundell · Razvan Pascanu · Matthew Botvinick
[ PDF] 
Oral
Wed Jul 11 08:40 AM -- 08:50 AM (PDT) @ A7
Synthesizing Robust Adversarial Examples
In Deep Learning (Adversarial) 1
Anish Athalye · Logan Engstrom · Andrew Ilyas · Kevin Kwok
[ PDF] 
Oral
Wed Jul 11 08:40 AM -- 08:50 AM (PDT) @ A1
Improved Regret Bounds for Thompson Sampling in Linear Quadratic Control Problems
In Reinforcement Learning 6
Marc Abeille · Alessandro Lazaric
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:40 AM -- 08:50 AM (PDT) @ K1 + K2
Learning Deep ResNet Blocks Sequentially using Boosting Theory
In Deep Learning (Theory) 2
Furong Huang · Jordan Ash · John Langford · Robert Schapire
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:50 AM -- 09:00 AM (PDT) @ A7
Adversarial Risk and the Dangers of Evaluating Against Weak Attacks
In Deep Learning (Adversarial) 1
Jonathan Uesato · Brendan O'Donoghue · Pushmeet Kohli · Aäron van den Oord
[ PDF] 
Oral
Wed Jul 11 08:50 AM -- 09:00 AM (PDT) @ A6
Fair and Diverse DPP-Based Data Summarization
In Society Impacts of Machine Learning 1
L. Elisa Celis · Vijay Keswani · Damian Straszak · Amit Jayant Deshpande · Tarun Kathuria · Nisheeth Vishnoi
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:50 AM -- 09:00 AM (PDT) @ K1 + K2
An Optimal Control Approach to Deep Learning and Applications to Discrete-Weight Neural Networks
In Deep Learning (Theory) 2
Qianxiao Li · IHPC Shuji Hao
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:50 AM -- 09:00 AM (PDT) @ A5
Neural Relational Inference for Interacting Systems
In Networks and Relational Learning 2
Thomas Kipf · Ethan Fetaya · Kuan-Chieh Wang · Max Welling · Richard Zemel
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:50 AM -- 09:00 AM (PDT) @ Victoria
Spline Filters For End-to-End Deep Learning
In Deep Learning (Neural Network Architectures) 5
Randall Balestriero · Romain Cosentino · Herve Glotin · Richard Baraniuk
[ PDF] 
Oral
Wed Jul 11 08:50 AM -- 09:00 AM (PDT) @ A4
Inference Suboptimality in Variational Autoencoders
In Approximate Inference 2
Chris Cremer · Xuechen Li · David Duvenaud
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:50 AM -- 09:00 AM (PDT) @ A3
Continual Reinforcement Learning with Complex Synapses
In Reinforcement Learning 7
Christos Kaplanis · Murray Shanahan · Claudia Clopath
[ PDF] 
Oral
Wed Jul 11 08:50 AM -- 09:00 AM (PDT) @ A1
Least-Squares Temporal Difference Learning for the Linear Quadratic Regulator
In Reinforcement Learning 6
Stephen Tu · Benjamin Recht
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:50 AM -- 09:00 AM (PDT) @ A9
A Simple Stochastic Variance Reduced Algorithm with Fast Convergence Rates
In Optimization (Convex) 2
Kaiwen Zhou · Fanhua Shang · James Cheng
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:50 AM -- 09:00 AM (PDT) @ K11
Bounds on the Approximation Power of Feedforward Neural Networks
In Optimization (Combinatorial) 2
Mohammad Mehrabi · Aslan Tchamkerten · MANSOOR I YOUSEFI
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:00 AM -- 02:20 AM (PDT) @ A9
Exploring Hidden Dimensions in Accelerating Convolutional Neural Networks
In Parallel and Distributed Learning 2
Zhihao Jia · Sina Lin · Charles Qi · Alex Aiken
[ PDF] 
Oral
Thu Jul 12 02:00 AM -- 02:20 AM (PDT) @ A3
Learning Policy Representations in Multiagent Systems
In Multi-Agent Learning 1
Aditya Grover · Maruan Al-Shedivat · Jayesh K. Gupta · Yura Burda · Harrison Edwards
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:00 AM -- 02:20 AM (PDT) @ A1
Convergent Tree Backup and Retrace with Function Approximation
In Reinforcement Learning 8
Ahmed Touati · Pierre-Luc Bacon · Doina Precup · Pascal Vincent
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:00 AM -- 02:20 AM (PDT) @ K1
Learning Memory Access Patterns
In Other Applications 2
Milad Hashemi · Kevin Swersky · Jamie Smith · Grant Ayers · Heiner Litz · Jichuan Chang · Christos Kozyrakis · Parthasarathy Ranganathan
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:00 AM -- 02:20 AM (PDT) @ K11
Probabilistic Boolean Tensor Decomposition
In Matrix Factorization 1
Tammo Rukat · Christopher Holmes · Christopher Yau
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:00 AM -- 02:20 AM (PDT) @ A4
Learning unknown ODE models with Gaussian processes
In Gaussian Processes 2
Markus Heinonen · Cagatay Yildiz · Henrik Mannerström · Jukka Intosalmi · Harri Lähdesmäki
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:00 AM -- 02:20 AM (PDT) @ A5
Learning Maximum-A-Posteriori Perturbation Models for Structured Prediction in Polynomial Time
In Structured Prediction 2
Asish Ghoshal · Jean Honorio
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:00 AM -- 02:20 AM (PDT) @ A6
Multicalibration: Calibration for the (Computationally-Identifiable) Masses
In Privacy, Anonymity, and Security 2
Ursula Hebert-Johnson · Michael Kim · Omer Reingold · Guy Rothblum
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:00 AM -- 02:20 AM (PDT) @ A7
Geometry Score: A Method For Comparing Generative Adversarial Networks
In Generative Models 2
Valentin Khrulkov · Ivan Oseledets
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:00 AM -- 02:20 AM (PDT) @ Victoria
Not to Cry Wolf: Distantly Supervised Multitask Learning in Critical Care
In Deep Learning (Neural Network Architectures) 6
Patrick Schwab · Emanuela Keller · Carl Muroi · David J. Mack · Christian Strässle · Walter Karlen
[ PDF] 
Oral
Thu Jul 12 02:20 AM -- 02:30 AM (PDT) @ K11
A Primal-Dual Analysis of Global Optimality in Nonconvex Low-Rank Matrix Recovery
In Matrix Factorization 1
Xiao Zhang · Lingxiao Wang · Yaodong Yu · Quanquan Gu
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:20 AM -- 02:40 AM (PDT) @ A5
Differentiable Dynamic Programming for Structured Prediction and Attention
In Structured Prediction 2
Arthur Mensch · Mathieu Blondel
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:20 AM -- 02:40 AM (PDT) @ Victoria
Compressing Neural Networks using the Variational Information Bottelneck
In Deep Learning (Neural Network Architectures) 6
Bin Dai · Chen Zhu · Baining Guo · David Wipf
[ PDF] 
Oral
Thu Jul 12 02:20 AM -- 02:40 AM (PDT) @ A4
Constraining the Dynamics of Deep Probabilistic Models
In Gaussian Processes 2
Marco Lorenzi · Maurizio Filippone
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:20 AM -- 02:40 AM (PDT) @ K1
Geodesic Convolutional Shape Optimization
In Other Applications 2
Pierre Baque · Edoardo Remelli · Francois Fleuret · EPFL Pascal Fua
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:20 AM -- 02:30 AM (PDT) @ A7
Optimizing the Latent Space of Generative Networks
In Generative Models 2
Piotr Bojanowski · Armand Joulin · David Lopez-Paz · Arthur Szlam
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:20 AM -- 02:30 AM (PDT) @ A3
Learning to Coordinate with Coordination Graphs in Repeated Single-Stage Multi-Agent Decision Problems
In Multi-Agent Learning 1
Eugenio Bargiacchi · Timothy Verstraeten · Diederik Roijers · Ann Nowé · Hado van Hasselt
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:20 AM -- 02:30 AM (PDT) @ A6
Residual Unfairness in Fair Machine Learning from Prejudiced Data
In Privacy, Anonymity, and Security 2
Nathan Kallus · Angela Zhou
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:20 AM -- 02:40 AM (PDT) @ A1
SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation
In Reinforcement Learning 8
Bo Dai · Albert Shaw · Lihong Li · Lin Xiao · Niao He · Zhen Liu · Jianshu Chen · Le Song
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:20 AM -- 02:40 AM (PDT) @ A9
Error Compensated Quantized SGD and its Applications to Large-scale Distributed Optimization
In Parallel and Distributed Learning 2
Jiaxiang Wu · Weidong Huang · Junzhou Huang · Tong Zhang
[ PDF] 
Oral
Thu Jul 12 02:30 AM -- 02:40 AM (PDT) @ A3
Learning to Act in Decentralized Partially Observable MDPs
In Multi-Agent Learning 1
Jilles Dibangoye · Olivier Buffet
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:30 AM -- 02:40 AM (PDT) @ A7
Adversarial Learning with Local Coordinate Coding
In Generative Models 2
Jiezhang Cao · Yong Guo · Qingyao Wu · Chunhua Shen · Junzhou Huang · Mingkui Tan
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:30 AM -- 02:40 AM (PDT) @ K11
Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval and Matrix Completion
In Matrix Factorization 1
Cong Ma · Kaizheng Wang · Yuejie Chi · Yuxin Chen
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:30 AM -- 02:40 AM (PDT) @ A6
Improving the Gaussian Mechanism for Differential Privacy: Analytical Calibration and Optimal Denoising
In Privacy, Anonymity, and Security 2
Borja de Balle Pigem · Yu-Xiang Wang
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:40 AM -- 02:50 AM (PDT) @ A3
Modeling Others using Oneself in Multi-Agent Reinforcement Learning
In Multi-Agent Learning 1
Roberta Raileanu · Emily Denton · Arthur Szlam · Facebook Rob Fergus
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:40 AM -- 02:50 AM (PDT) @ Victoria
Kernelized Synaptic Weight Matrices
In Deep Learning (Neural Network Architectures) 6
Lorenz Müller · Julien Martel · Giacomo Indiveri
[ PDF] 
Oral
Thu Jul 12 02:40 AM -- 02:50 AM (PDT) @ A5
Structured Output Learning with Abstention: Application to Accurate Opinion Prediction
In Structured Prediction 2
Alexandre Garcia · Telecom-ParisTech Chloé Clavel · Slim Essid · Florence d'Alche-Buc
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:40 AM -- 02:50 AM (PDT) @ K11
Learning Binary Latent Variable Models: A Tensor Eigenpair Approach
In Matrix Factorization 1
Ariel Jaffe · Roi Weiss · Boaz Nadler · Shai Carmi · Yuval Kluger
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:40 AM -- 02:50 AM (PDT) @ A4
Probabilistic Recurrent State-Space Models
In Gaussian Processes 2
Andreas Doerr · Christian Daniel · Martin Schiegg · Duy Nguyen-Tuong · Stefan Schaal · Marc Toussaint · Sebastian Trimpe
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:40 AM -- 02:50 AM (PDT) @ A1
Scalable Bilinear Pi Learning Using State and Action Features
In Reinforcement Learning 8
Yichen Chen · Lihong Li · Mengdi Wang
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:40 AM -- 02:50 AM (PDT) @ A6
Improving the Privacy and Accuracy of ADMM-Based Distributed Algorithms
In Privacy, Anonymity, and Security 2
Xueru Zhang · Mohammad Mahdi Khalili · Mingyan Liu
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:40 AM -- 02:50 AM (PDT) @ A9
DICOD: Distributed Convolutional Coordinate Descent for Convolutional Sparse Coding
In Parallel and Distributed Learning 2
Thomas Moreau · Laurent Oudre · Nicolas Vayatis
[ PDF] 
Oral
Thu Jul 12 02:40 AM -- 02:50 AM (PDT) @ A7
Learning Representations and Generative Models for 3D Point Clouds
In Generative Models 2
Panagiotis Achlioptas · Olga Diamanti · Ioannis Mitliagkas · Leonidas Guibas
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:40 AM -- 02:50 AM (PDT) @ K1
AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization with Structured Kernel Learning
In Other Applications 2
Ahmed M. Alaa · Mihaela van der Schaar
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:50 AM -- 03:00 AM (PDT) @ Victoria
Deep Models of Interactions Across Sets
In Deep Learning (Neural Network Architectures) 6
Jason Hartford · Devon Graham · Kevin Leyton-Brown · Siamak Ravanbakhsh
[ PDF] 
Oral
Thu Jul 12 02:50 AM -- 03:00 AM (PDT) @ A3
QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
In Multi-Agent Learning 1
Tabish Rashid · Mikayel Samvelyan · Christian Schroeder · Gregory Farquhar · Jakob Foerster · Shimon Whiteson
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:50 AM -- 03:00 AM (PDT) @ A7
Theoretical Analysis of Image-to-Image Translation with Adversarial Learning
In Generative Models 2
Xudong Pan · Mi Zhang · Daizong Ding
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:50 AM -- 03:00 AM (PDT) @ A4
Structured Variationally Auto-encoded Optimization
In Gaussian Processes 2
Xiaoyu Lu · Javier González · Zhenwen Dai · Neil Lawrence
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:50 AM -- 03:00 AM (PDT) @ K1
TAPAS: Tricks to Accelerate (encrypted) Prediction As a Service
In Other Applications 2
Amartya Sanyal · Matt Kusner · Adria Gascon · Varun Kanade
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:50 AM -- 03:00 AM (PDT) @ A9
Distributed Asynchronous Optimization with Unbounded Delays: How Slow Can You Go?
In Parallel and Distributed Learning 2
Zhengyuan Zhou · Panayotis Mertikopoulos · Nicholas Bambos · Peter Glynn · Yinyu Ye · Li-Jia Li · Li Fei-Fei
[ PDF] 
Oral
Thu Jul 12 02:50 AM -- 03:00 AM (PDT) @ K11
Closed-form Marginal Likelihood in Gamma-Poisson Matrix Factorization
In Matrix Factorization 1
Louis Filstroff · Alberto Lumbreras · Cedric Fevotte
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:50 AM -- 03:00 AM (PDT) @ A1
Stochastic Variance-Reduced Policy Gradient
In Reinforcement Learning 8
Matteo Papini · Damiano Binaghi · Giuseppe Canonaco · Matteo Pirotta · Marcello Restelli
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:50 AM -- 03:00 AM (PDT) @ A6
Adversarial Regression with Multiple Learners
In Privacy, Anonymity, and Security 2
Liang Tong · Sixie Yu · Scott Alfeld · Yevgeniy Vorobeychik
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:50 AM -- 03:00 AM (PDT) @ A5
End-to-End Learning for the Deep Multivariate Probit Model
In Structured Prediction 2
Di Chen · Yexiang Xue · Carla Gomes
[ PDF]  [ Video] 
Oral
Thu Jul 12 04:30 AM -- 04:50 AM (PDT) @ A3
Fast Information-theoretic Bayesian Optimisation
In Optimization (Bayesian) 2
Binxin Ru · Michael A Osborne · Mark Mcleod · Diego Granziol
[ PDF]  [ Video] 
Oral
Thu Jul 12 04:30 AM -- 04:50 AM (PDT) @ A1
Investigating Human Priors for Playing Video Games
In Reinforcement Learning 9
Rachit Dubey · Pulkit Agrawal · Deepak Pathak · Tom Griffiths · Alexei Efros
[ PDF]  [ Video] 
Oral
Thu Jul 12 04:30 AM -- 04:50 AM (PDT) @ A6
Inductive Two-Layer Modeling with Parametric Bregman Transfer
In Supervised Learning 1
Vignesh Ganapathiraman · Zhan Shi · Xinhua Zhang · Yaoliang Yu
[ PDF]  [ Video] 
Oral
Thu Jul 12 04:30 AM -- 04:50 AM (PDT) @ A7
Composite Functional Gradient Learning of Generative Adversarial Models
In Deep Learning (Adversarial) 2
Rie Johnson · Tong Zhang
[ PDF]  [ Video] 
Oral
Thu Jul 12 04:30 AM -- 04:50 AM (PDT) @ A4
Error Estimation for Randomized Least-Squares Algorithms via the Bootstrap
In Monte Carlo Methods 1
Miles Lopes · Shusen Wang · Michael Mahoney
[ PDF]  [ Video] 
Oral
Thu Jul 12 04:30 AM -- 04:50 AM (PDT) @ A5
Accelerated Spectral Ranking
In Ranking and Preference Learning 2
Arpit Agarwal · Prathamesh Patil · Shivani Agarwal
[ PDF]  [ Video] 
Oral
Thu Jul 12 04:30 AM -- 04:50 AM (PDT) @ K1
Learning One Convolutional Layer with Overlapping Patches
In Deep Learning (Theory) 3
Surbhi Goel · Adam Klivans · Raghu Meka
[ PDF]  [ Video] 
Oral
Thu Jul 12 04:30 AM -- 04:50 AM (PDT) @ Victoria
Focused Hierarchical RNNs for Conditional Sequence Processing
In Deep Learning (Neural Network Architectures) 7
Rosemary Nan Ke · Konrad Zolna · Alessandro Sordoni · Zhouhan Lin · Adam Trischler · Yoshua Bengio · Joelle Pineau · Laurent Charlin · Christopher Pal
[ PDF] 
Oral
Thu Jul 12 04:30 AM -- 04:50 AM (PDT) @ K11
Improved large-scale graph learning through ridge spectral sparsification
In Large Scale Learning and Big Data 1
Daniele Calandriello · Alessandro Lazaric · Ioannis Koutis · Michal Valko
[ PDF]  [ Video] 
Oral
Thu Jul 12 04:30 AM -- 04:50 AM (PDT) @ A9
Shampoo: Preconditioned Stochastic Tensor Optimization
In Optimization (Convex) 3
Vineet Gupta · Tomer Koren · Yoram Singer
[ PDF] 
Oral
Thu Jul 12 04:50 AM -- 05:10 AM (PDT) @ A3
Optimization, fast and slow: optimally switching between local and Bayesian optimization
In Optimization (Bayesian) 2
Mark McLeod · Stephen Roberts · Michael A Osborne
[ PDF]  [ Video] 
Oral
Thu Jul 12 04:50 AM -- 05:00 AM (PDT) @ A6
Does Distributionally Robust Supervised Learning Give Robust Classifiers?
In Supervised Learning 1
Weihua Hu · Gang Niu · Issei Sato · Masashi Sugiyama
[ PDF]  [ Video] 
Oral
Thu Jul 12 04:50 AM -- 05:00 AM (PDT) @ A5
Composite Marginal Likelihood Methods for Random Utility Models
In Ranking and Preference Learning 2
Zhibing Zhao · Lirong Xia
[ PDF]  [ Video] 
Oral
Thu Jul 12 04:50 AM -- 05:00 AM (PDT) @ A9
Characterizing Implicit Bias in Terms of Optimization Geometry
In Optimization (Convex) 3
Suriya Gunasekar · Jason Lee · Daniel Soudry · Nati Srebro
[ PDF] 
Oral
Thu Jul 12 04:50 AM -- 05:10 AM (PDT) @ K11
Parallel and Streaming Algorithms for K-Core Decomposition
In Large Scale Learning and Big Data 1
Hossein Esfandiari · Silvio Lattanzi · Vahab Mirrokni
[ PDF]  [ Video] 
Oral
Thu Jul 12 04:50 AM -- 05:00 AM (PDT) @ A4
Asynchronous Stochastic Quasi-Newton MCMC for Non-Convex Optimization
In Monte Carlo Methods 1
Umut Simsekli · Cagatay Yildiz · Thanh Huy Nguyen · Ali Taylan Cemgil · Gaël RICHARD
[ PDF]  [ Video] 
Oral
Thu Jul 12 04:50 AM -- 05:00 AM (PDT) @ A7
Tempered Adversarial Networks
In Deep Learning (Adversarial) 2
Mehdi S. M. Sajjadi · Giambattista Parascandolo · Arash Mehrjou · Bernhard Schölkopf
[ PDF]  [ Video] 
Oral
Thu Jul 12 04:50 AM -- 05:00 AM (PDT) @ A1
Can Deep Reinforcement Learning Solve Erdos-Selfridge-Spencer Games?
In Reinforcement Learning 9
Maithra Raghu · Alexander Irpan · Jacob Andreas · Bobby Kleinberg · Quoc Le · Jon Kleinberg
[ PDF]  [ Video] 
Oral
Thu Jul 12 04:50 AM -- 05:10 AM (PDT) @ Victoria
Learn from Your Neighbor: Learning Multi-modal Mappings from Sparse Annotations
In Deep Learning (Neural Network Architectures) 7
Ashwin Kalyan · Stefan Lee · Anitha Kannan · Dhruv Batra
[ PDF] 
Oral
Thu Jul 12 04:50 AM -- 05:10 AM (PDT) @ K1
Gradient Descent Learns One-hidden-layer CNN: Don't be Afraid of Spurious Local Minima
In Deep Learning (Theory) 3
Simon Du · Jason Lee · Yuandong Tian · Aarti Singh · Barnabás Póczos
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:00 AM -- 05:10 AM (PDT) @ A1
GEP-PG: Decoupling Exploration and Exploitation in Deep Reinforcement Learning Algorithms
In Reinforcement Learning 9
Cédric Colas · Olivier Sigaud · Pierre-Yves Oudeyer
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:00 AM -- 05:10 AM (PDT) @ A9
A Distributed Second-Order Algorithm You Can Trust
In Optimization (Convex) 3
Celestine Mendler-Dünner · Aurelien Lucchi · Matilde Gargiani · Yatao Bian · Thomas Hofmann · Martin Jaggi
[ PDF] 
Oral
Thu Jul 12 05:00 AM -- 05:10 AM (PDT) @ A4
Stochastic Variance-Reduced Hamilton Monte Carlo Methods
In Monte Carlo Methods 1
Difan Zou · Pan Xu · Quanquan Gu
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:00 AM -- 05:10 AM (PDT) @ A5
Ranking Distributions based on Noisy Sorting
In Ranking and Preference Learning 2
Adil El Mesaoudi-Paul · Eyke Hüllermeier · Robert Busa-Fekete
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:00 AM -- 05:10 AM (PDT) @ A7
Improved Training of Generative Adversarial Networks Using Representative Features
In Deep Learning (Adversarial) 2
Duhyeon Bang · Hyunjung Shim
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:00 AM -- 05:10 AM (PDT) @ A6
Prediction Rule Reshaping
In Supervised Learning 1
Matt Bonakdarpour · Sabyasachi Chatterjee · Rina Barber · John Lafferty
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:10 AM -- 05:20 AM (PDT) @ A3
Batch Bayesian Optimization via Multi-objective Acquisition Ensemble for Automated Analog Circuit Design
In Optimization (Bayesian) 2
Wenlong Lyu · Fan Yang · Changhao Yan · Dian Zhou · Xuan Zeng
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:10 AM -- 05:20 AM (PDT) @ A5
SQL-Rank: A Listwise Approach to Collaborative Ranking
In Ranking and Preference Learning 2
LIWEI WU · Cho-Jui Hsieh · University of California James Sharpnack
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:10 AM -- 05:20 AM (PDT) @ A4
A Robust Approach to Sequential Information Theoretic Planning
In Monte Carlo Methods 1
Sue Zheng · Jason Pacheco · John Fisher
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:10 AM -- 05:20 AM (PDT) @ K11
Fast Approximate Spectral Clustering for Dynamic Networks
In Large Scale Learning and Big Data 1
Lionel Martin · Andreas Loukas · Pierre Vandergheynst
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:10 AM -- 05:20 AM (PDT) @ A6
Finding Influential Training Samples for Gradient Boosted Decision Trees
In Supervised Learning 1
Boris Sharchilev · Yury Ustinovskiy · Pavel Serdyukov · Maarten de Rijke
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:10 AM -- 05:20 AM (PDT) @ A7
A Two-Step Computation of the Exact GAN Wasserstein Distance
In Deep Learning (Adversarial) 2
Huidong Liu · Xianfeng GU · Samaras Dimitris
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:10 AM -- 05:20 AM (PDT) @ Victoria
Learning long term dependencies via Fourier recurrent units
In Deep Learning (Neural Network Architectures) 7
Jiong Zhang · Yibo Lin · Zhao Song · Inderjit Dhillon
[ PDF] 
Oral
Thu Jul 12 05:10 AM -- 05:20 AM (PDT) @ A9
A Delay-tolerant Proximal-Gradient Algorithm for Distributed Learning
In Optimization (Convex) 3
Konstantin Mishchenko · Franck Iutzeler · Jérôme Malick · Massih-Reza Amini
[ PDF] 
Oral
Thu Jul 12 05:10 AM -- 05:20 AM (PDT) @ A1
Time Limits in Reinforcement Learning
In Reinforcement Learning 9
Fabio Pardo · Arash Tavakoli · Vitaly Levdik · Petar Kormushev
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:10 AM -- 05:20 AM (PDT) @ K1
The Multilinear Structure of ReLU Networks
In Deep Learning (Theory) 3
Thomas Laurent · James von Brecht
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:20 AM -- 05:30 AM (PDT) @ A1
Visualizing and Understanding Atari Agents
In Reinforcement Learning 9
Samuel Greydanus · Anurag Koul · Jonathan Dodge · Alan Fern
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:20 AM -- 05:30 AM (PDT) @ K1
Understanding the Loss Surface of Neural Networks for Binary Classification
In Deep Learning (Theory) 3
SHIYU LIANG · Ruoyu Sun · Yixuan Li · R Srikant
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:20 AM -- 05:30 AM (PDT) @ A3
Tight Regret Bounds for Bayesian Optimization in One Dimension
In Optimization (Bayesian) 2
Jonathan Scarlett
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:20 AM -- 05:30 AM (PDT) @ A7
Is Generator Conditioning Causally Related to GAN Performance?
In Deep Learning (Adversarial) 2
Augustus Odena · Jacob Buckman · Catherine Olsson · Tom B Brown · Christopher Olah · Colin Raffel · Ian Goodfellow
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:20 AM -- 05:30 AM (PDT) @ A6
Noise2Noise: Learning Image Restoration without Clean Data
In Supervised Learning 1
Jaakko Lehtinen · Jacob Munkberg · Jon Hasselgren · Samuli Laine · Tero Karras · Miika Aittala · Timo Aila
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:20 AM -- 05:30 AM (PDT) @ K11
Matrix Norms in Data Streams: Faster, Multi-Pass and Row-Order
In Large Scale Learning and Big Data 1
Vladimir Braverman · Stephen Chestnut · Robert Krauthgamer · Yi Li · David Woodruff · Lin Yang
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:20 AM -- 05:30 AM (PDT) @ A4
Discrete-Continuous Mixtures in Probabilistic Programming: Generalized Semantics and Inference Algorithms
In Monte Carlo Methods 1
Yi Wu · Siddharth Srivastava · Nicholas Hay · Simon Du · Stuart Russell
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:20 AM -- 05:30 AM (PDT) @ A5
Extreme Learning to Rank via Low Rank Assumption
In Ranking and Preference Learning 2
Minhao Cheng · Ian Davidson · Cho-Jui Hsieh
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:20 AM -- 05:30 AM (PDT) @ A9
Gradient Coding from Cyclic MDS Codes and Expander Graphs
In Optimization (Convex) 3
Netanel Raviv · Rashish Tandon · Alexandros Dimakis · Itzhak Tamo
[ PDF] 
Oral
Thu Jul 12 05:20 AM -- 05:30 AM (PDT) @ Victoria
Training Neural Machines with Trace-Based Supervision
In Deep Learning (Neural Network Architectures) 7
Matthew Mirman · Dimitar Dimitrov · Pavle Djordjevic · Timon Gehr · Martin Vechev
[ PDF] 
Oral
Thu Jul 12 05:30 AM -- 05:50 AM (PDT) @ Victoria
Neural Dynamic Programming for Musical Self Similarity
In Deep Learning (Neural Network Architectures) 8
Christian Walder · Dongwoo Kim
[ PDF] 
Oral
Thu Jul 12 05:30 AM -- 05:50 AM (PDT) @ A9
Alternating Randomized Block Coordinate Descent
In Optimization (Convex) 4
Jelena Diakonikolas · Orecchia Lorenzo
[ PDF] 
Oral
Thu Jul 12 05:30 AM -- 05:50 AM (PDT) @ A7
Black-box Adversarial Attacks with Limited Queries and Information
In Deep Learning (Adversarial) 3
Andrew Ilyas · Logan Engstrom · Anish Athalye · Jessy Lin
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:30 AM -- 05:50 AM (PDT) @ A6
Dimensionality-Driven Learning with Noisy Labels
In Supervised Learning 2
Xingjun Ma · Yisen Wang · Michael E. Houle · Shuo Zhou · Sarah Erfani · Shutao Xia · Sudanthi Wijewickrema · James Bailey
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:30 AM -- 05:50 AM (PDT) @ K11
Near Optimal Frequent Directions for Sketching Dense and Sparse Matrices
In Large Scale Learning and Big Data 2
Zengfeng Huang
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:30 AM -- 05:50 AM (PDT) @ A3
To Understand Deep Learning We Need to Understand Kernel Learning
In Kernel Methods 1
Mikhail Belkin · Siyuan Ma · Soumik Mandal
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:30 AM -- 05:50 AM (PDT) @ A5
Feasible Arm Identification
In Online Learning 1
Julian Katz-Samuels · Clay Scott
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:30 AM -- 05:50 AM (PDT) @ K1
Tropical Geometry of Deep Neural Networks
In Deep Learning (Theory) 4
Liwen Zhang · Gregory Naisat · Lek-Heng Lim
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:30 AM -- 05:50 AM (PDT) @ A4
Robust and Scalable Models of Microbiome Dynamics
In Graphical Models 1
Travis Gibson · Georg Gerber
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:30 AM -- 05:50 AM (PDT) @ A1
The Mirage of Action-Dependent Baselines in Reinforcement Learning
In Reinforcement Learning 10
George Tucker · Surya Bhupatiraju · Shixiang Gu · Richard E Turner · Zoubin Ghahramani · Sergey Levine
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:50 AM -- 06:10 AM (PDT) @ A5
Bandits with Delayed, Aggregated Anonymous Feedback
In Online Learning 1
Ciara Pike-Burke · Shipra Agrawal · Csaba Szepesvari · Steffen Grünewälder
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:50 AM -- 06:10 AM (PDT) @ A9
Randomized Block Cubic Newton Method
In Optimization (Convex) 4
Nikita Doikov · Peter Richtarik
[ PDF] 
Oral
Thu Jul 12 05:50 AM -- 06:00 AM (PDT) @ Victoria
A Hierarchical Latent Vector Model for Learning Long-Term Structure in Music
In Deep Learning (Neural Network Architectures) 8
Adam Roberts · Jesse Engel · Colin Raffel · Curtis Hawthorne · Douglas Eck
[ PDF] 
Oral
Thu Jul 12 05:50 AM -- 06:10 AM (PDT) @ A7
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples
In Deep Learning (Adversarial) 3
Anish Athalye · Nicholas Carlini · David Wagner
[ PDF] 
Oral
Thu Jul 12 05:50 AM -- 06:10 AM (PDT) @ A3
Kernel Recursive ABC: Point Estimation with Intractable Likelihood
In Kernel Methods 1
Takafumi Kajihara · Motonobu Kanagawa · Keisuke Yamazaki · Kenji Fukumizu
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:50 AM -- 06:10 AM (PDT) @ A1
Smoothed Action Value Functions for Learning Gaussian Policies
In Reinforcement Learning 10
Ofir Nachum · Mohammad Norouzi · George Tucker · Dale Schuurmans
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:50 AM -- 06:00 AM (PDT) @ A6
MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels
In Supervised Learning 2
Lu Jiang · Zhengyuan Zhou · Thomas Leung · Li-Jia Li · Li Fei-Fei
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:50 AM -- 06:00 AM (PDT) @ A4
Stein Variational Message Passing for Continuous Graphical Models
In Graphical Models 1
Dilin Wang · Zhe Zeng · Qiang Liu
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:50 AM -- 06:10 AM (PDT) @ K1
A Spline Theory of Deep Learning
In Deep Learning (Theory) 4
Randall Balestriero · Richard Baraniuk
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:50 AM -- 06:00 AM (PDT) @ K11
Loss Decomposition for Fast Learning in Large Output Spaces
In Large Scale Learning and Big Data 2
En-Hsu Yen · Satyen Kale · Felix Xinnan Yu · Daniel Holtmann-Rice · Sanjiv Kumar · Pradeep Ravikumar
[ PDF]  [ Video] 
Oral
Thu Jul 12 06:00 AM -- 06:10 AM (PDT) @ A6
Learning to Reweight Examples for Robust Deep Learning
In Supervised Learning 2
Mengye Ren · Wenyuan Zeng · Bin Yang · Raquel Urtasun
[ PDF]  [ Video] 
Oral
Thu Jul 12 06:00 AM -- 06:10 AM (PDT) @ Victoria
Fast Decoding in Sequence Models Using Discrete Latent Variables
In Deep Learning (Neural Network Architectures) 8
Lukasz Kaiser · Samy Bengio · Aurko Roy · Ashish Vaswani · Niki Parmar · Jakob Uszkoreit · Noam Shazeer
[ PDF] 
Oral
Thu Jul 12 06:00 AM -- 06:10 AM (PDT) @ A4
A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models
In Graphical Models 1
Beilun Wang · Arshdeep Sekhon · Yanjun Qi
[ PDF]  [ Video] 
Oral
Thu Jul 12 06:00 AM -- 06:10 AM (PDT) @ K11
Ultra Large-Scale Feature Selection using Count-Sketches
In Large Scale Learning and Big Data 2
Amirali Aghazadeh · Ryan Spring · Daniel LeJeune · Gautam Dasarathy · Anshumali Shrivastava · Richard Baraniuk
[ PDF]  [ Video] 
Oral
Thu Jul 12 06:10 AM -- 06:20 AM (PDT) @ A3
Differentially Private Database Release via Kernel Mean Embeddings
In Kernel Methods 1
Matej Balog · Ilya Tolstikhin · Bernhard Schölkopf
[ PDF]  [ Video] 
Oral
Thu Jul 12 06:10 AM -- 06:20 AM (PDT) @ A1
Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor
In Reinforcement Learning 10
Tuomas Haarnoja · Aurick Zhou · Pieter Abbeel · Sergey Levine
[ PDF] 
Oral
Thu Jul 12 06:10 AM -- 06:20 AM (PDT) @ A5
Make the Minority Great Again: First-Order Regret Bound for Contextual Bandits
In Online Learning 1
Zeyuan Allen-Zhu · Sebastien Bubeck · Yuanzhi Li
[ PDF]  [ Video] 
Oral
Thu Jul 12 06:10 AM -- 06:20 AM (PDT) @ A4
Large-Scale Sparse Inverse Covariance Estimation via Thresholding and Max-Det Matrix Completion
In Graphical Models 1
Richard Zhang · Salar Fattahi · Somayeh Sojoudi
[ PDF]  [ Video] 
Oral
Thu Jul 12 06:10 AM -- 06:20 AM (PDT) @ Victoria
PixelSNAIL: An Improved Autoregressive Generative Model
In Deep Learning (Neural Network Architectures) 8
Xi Chen · Nikhil Mishra · Mostafa Rohaninejad · Pieter Abbeel
[ PDF] 
Oral
Thu Jul 12 06:10 AM -- 06:20 AM (PDT) @ A9
Accelerating Greedy Coordinate Descent Methods
In Optimization (Convex) 4
Haihao Lu · Robert Freund · Vahab Mirrokni
[ PDF] 
Oral
Thu Jul 12 06:10 AM -- 06:20 AM (PDT) @ K11
Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions
In Large Scale Learning and Big Data 2
Shuaiwen Wang · Wenda Zhou · Haihao Lu · Arian Maleki · Vahab Mirrokni
[ PDF]  [ Video] 
Oral
Thu Jul 12 06:10 AM -- 06:20 AM (PDT) @ K1
Neural Networks Should Be Wide Enough to Learn Disconnected Decision Regions
In Deep Learning (Theory) 4
Quynh Nguyen · Mahesh Mukkamala · Matthias Hein
[ PDF]  [ Video] 
Oral
Thu Jul 12 06:10 AM -- 06:20 AM (PDT) @ A7
Adversarial Attack on Graph Structured Data
In Deep Learning (Adversarial) 3
Hanjun Dai · Hui Li · Tian Tian · Xin Huang · Lin Wang · Jun Zhu · Le Song
[ PDF] 
Oral
Thu Jul 12 06:10 AM -- 06:20 AM (PDT) @ A6
Curriculum Learning by Transfer Learning: Theory and Experiments with Deep Networks
In Supervised Learning 2
Daphna Weinshall · Gad A Cohen · Dan Amir
[ PDF]  [ Video] 
Oral
Thu Jul 12 06:20 AM -- 06:30 AM (PDT) @ A3
Learning in Reproducing Kernel Kreı̆n Spaces
In Kernel Methods 1
Dino Oglic · Thomas Gaertner
[ PDF]  [ Video] 
Oral
Thu Jul 12 06:20 AM -- 06:30 AM (PDT) @ A4
Bucket Renormalization for Approximate Inference
In Graphical Models 1
Sungsoo Ahn · Michael Chertkov · Adrian Weller · Jinwoo Shin
[ PDF]  [ Video] 
Oral
Thu Jul 12 06:20 AM -- 06:30 AM (PDT) @ A6
Improving Regression Performance with Distributional Losses
In Supervised Learning 2
Ehsan Imani · Martha White
[ PDF]  [ Video] 
Oral
Thu Jul 12 06:20 AM -- 06:30 AM (PDT) @ K1
Stronger Generalization Bounds for Deep Nets via a Compression Approach
In Deep Learning (Theory) 4
Sanjeev Arora · Rong Ge · Behnam Neyshabur · Yi Zhang
[ PDF]  [ Video] 
Oral
Thu Jul 12 06:20 AM -- 06:30 AM (PDT) @ A1
Addressing Function Approximation Error in Actor-Critic Methods
In Reinforcement Learning 10
Scott Fujimoto · Herke van Hoof · David Meger
[ PDF]  [ Video] 
Oral
Thu Jul 12 06:20 AM -- 06:30 AM (PDT) @ A9
On Acceleration with Noise-Corrupted Gradients
In Optimization (Convex) 4
Michael Cohen · Jelena Diakonikolas · Orecchia Lorenzo
[ PDF] 
Oral
Thu Jul 12 06:20 AM -- 06:30 AM (PDT) @ A7
GAIN: Missing Data Imputation using Generative Adversarial Nets
In Deep Learning (Adversarial) 3
Jinsung Yoon · James Jordon · Mihaela van der Schaar
[ PDF] 
Oral
Thu Jul 12 06:20 AM -- 06:30 AM (PDT) @ Victoria
Image Transformer
In Deep Learning (Neural Network Architectures) 8
Niki Parmar · Ashish Vaswani · Jakob Uszkoreit · Lukasz Kaiser · Noam Shazeer · Alexander Ku · Dustin Tran
[ PDF] 
Oral
Thu Jul 12 06:20 AM -- 06:30 AM (PDT) @ K11
Semi-Supervised Learning on Data Streams via Temporal Label Propagation
In Large Scale Learning and Big Data 2
Tal Wagner · Sudipto Guha · Shiva Kasiviswanathan · Nina Mishra
[ PDF]  [ Video] 
Oral
Thu Jul 12 06:20 AM -- 06:30 AM (PDT) @ A5
Thompson Sampling for Combinatorial Semi-Bandits
In Online Learning 1
Siwei Wang · Wei Chen
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:00 AM -- 07:20 AM (PDT) @ A1
Configurable Markov Decision Processes
In Reinforcement Learning 11
Alberto Maria Metelli · Mirco Mutti · Marcello Restelli
[ PDF] 
Oral
Thu Jul 12 07:00 AM -- 07:20 AM (PDT) @ A9
Approximate message passing for amplitude based optimization
In Optimization (Non-convex) 3
Junjie Ma · Ji Xu · Arian Maleki
[ PDF] 
Oral
Thu Jul 12 07:00 AM -- 07:20 AM (PDT) @ Victoria
Using Inherent Structures to design Lean 2-layer RBMs
In Deep Learning (Neural Network Architectures) 9
Abhishek Bansal · Abhinav Anand · Chiranjib Bhattacharyya
[ PDF] 
Oral
Thu Jul 12 07:00 AM -- 07:20 AM (PDT) @ K1
Reviving and Improving Recurrent Back-Propagation
In Deep Learning (Theory) 5
Renjie Liao · Yuwen Xiong · Ethan Fetaya · Lisa Zhang · KiJung Yoon · Zachary S Pitkow · Raquel Urtasun · Richard Zemel
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:00 AM -- 07:20 AM (PDT) @ K11
Decentralized Submodular Maximization: Bridging Discrete and Continuous Settings
In Optimization (Combinatorial) 3
Aryan Mokhtari · Hamed Hassani · Amin Karbasi
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:00 AM -- 07:20 AM (PDT) @ A6
Optimal Distributed Learning with Multi-pass Stochastic Gradient Methods
In Statistical Learning Theory 4
Junhong Lin · Volkan Cevher
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:00 AM -- 07:20 AM (PDT) @ A3
Towards End-to-End Prosody Transfer for Expressive Speech Synthesis with Tacotron
In Natural Language and Speech Processing 1
RJ Skerry-Ryan · Eric Battenberg · Ying Xiao · Yuxuan Wang · Daisy Stanton · Joel Shor · Ron Weiss · Robert Clark · Rif Saurous
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:00 AM -- 07:20 AM (PDT) @ A5
Projection-Free Online Optimization with Stochastic Gradient: From Convexity to Submodularity
In Online Learning 2
Lin Chen · Christopher Harshaw · Hamed Hassani · Amin Karbasi
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:00 AM -- 07:20 AM (PDT) @ A4
Variational Bayesian dropout: pitfalls and fixes
In Deep Learning (Bayesian) 2
Jiri Hron · Alexander Matthews · Zoubin Ghahramani
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:00 AM -- 07:20 AM (PDT) @ A7
The Mechanics of n-Player Differentiable Games
In Deep Learning (Adversarial) 4
David Balduzzi · Sebastien Racaniere · James Martens · Jakob Foerster · Karl Tuyls · Thore Graepel
[ PDF] 
Oral
Thu Jul 12 07:20 AM -- 07:40 AM (PDT) @ A3
Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis
In Natural Language and Speech Processing 1
Yuxuan Wang · Daisy Stanton · Yu Zhang · RJ-Skerry Ryan · Eric Battenberg · Joel Shor · Ying Xiao · Ye Jia · Fei Ren · Rif Saurous
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:20 AM -- 07:30 AM (PDT) @ K11
Approximation Guarantees for Adaptive Sampling
In Optimization (Combinatorial) 3
Eric Balkanski · Yaron Singer
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:20 AM -- 07:40 AM (PDT) @ A9
Dissecting Adam: The Sign, Magnitude and Variance of Stochastic Gradients
In Optimization (Non-convex) 3
Lukas Balles · Philipp Hennig
[ PDF] 
Oral
Thu Jul 12 07:20 AM -- 07:30 AM (PDT) @ A4
Accurate Uncertainties for Deep Learning Using Calibrated Regression
In Deep Learning (Bayesian) 2
Volodymyr Kuleshov · Nathan Fenner · Stefano Ermon
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:20 AM -- 07:40 AM (PDT) @ A6
Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates
In Statistical Learning Theory 4
Dong Yin · Yudong Chen · Kannan Ramchandran · Peter Bartlett
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:20 AM -- 07:30 AM (PDT) @ A7
K-Beam Minimax: Efficient Optimization for Deep Adversarial Learning
In Deep Learning (Adversarial) 4
Jihun Hamm · Yung-Kyun Noh
[ PDF] 
Oral
Thu Jul 12 07:20 AM -- 07:40 AM (PDT) @ A1
Beyond the One-Step Greedy Approach in Reinforcement Learning
In Reinforcement Learning 11
Yonathan Efroni · Gal Dalal · Bruno Scherrer · Shie Mannor
[ PDF] 
Oral
Thu Jul 12 07:20 AM -- 07:30 AM (PDT) @ Victoria
Deep Asymmetric Multi-task Feature Learning
In Deep Learning (Neural Network Architectures) 9
Hae Beom Lee · Eunho Yang · Sung Ju Hwang
[ PDF] 
Oral
Thu Jul 12 07:20 AM -- 07:30 AM (PDT) @ K1
Dynamical Isometry and a Mean Field Theory of RNNs: Gating Enables Signal Propagation in Recurrent Neural Networks
In Deep Learning (Theory) 5
Minmin Chen · Jeffrey Pennington · Samuel Schoenholz
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:20 AM -- 07:40 AM (PDT) @ A5
Practical Contextual Bandits with Regression Oracles
In Online Learning 2
Dylan Foster · Alekh Agarwal · Miroslav Dudik · Haipeng Luo · Robert Schapire
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:30 AM -- 07:40 AM (PDT) @ Victoria
Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations
In Deep Learning (Neural Network Architectures) 9
Yiping Lu · Aoxiao Zhong · Quanzheng Li · Bin Dong
[ PDF] 
Oral
Thu Jul 12 07:30 AM -- 07:40 AM (PDT) @ A4
Decomposition of Uncertainty in Bayesian Deep Learning for Efficient and Risk-sensitive Learning
In Deep Learning (Bayesian) 2
Stefan Depeweg · Jose Miguel Hernandez-Lobato · Finale Doshi-Velez · Steffen Udluft
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:30 AM -- 07:40 AM (PDT) @ K11
Greed is Still Good: Maximizing Monotone Submodular+Supermodular (BP) Functions
In Optimization (Combinatorial) 3
Wenruo Bai · Jeff Bilmes
[ PDF] 
Oral
Thu Jul 12 07:30 AM -- 07:40 AM (PDT) @ A7
First Order Generative Adversarial Networks
In Deep Learning (Adversarial) 4
Calvin Seward · Thomas Unterthiner · Urs M Bergmann · Nikolay Jetchev · Sepp Hochreiter
[ PDF] 
Oral
Thu Jul 12 07:30 AM -- 07:40 AM (PDT) @ K1
Invariance of Weight Distributions in Rectified MLPs
In Deep Learning (Theory) 5
Susumu Tsuchida · Fred Roosta · Marcus Gallagher
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:40 AM -- 07:50 AM (PDT) @ A5
Fast Stochastic AUC Maximization with $O(1/n)$-Convergence Rate
In Online Learning 2
Mingrui Liu · Xiaoxuan Zhang · Zaiyi Chen · Xiaoyu Wang · Tianbao Yang
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:40 AM -- 07:50 AM (PDT) @ A7
Towards Fast Computation of Certified Robustness for ReLU Networks
In Deep Learning (Adversarial) 4
Tsui-Wei Weng · Huan Zhang · Hongge Chen · Zhao Song · Cho-Jui Hsieh · Luca Daniel · Duane Boning · Inderjit Dhillon
[ PDF] 
Oral
Thu Jul 12 07:40 AM -- 07:50 AM (PDT) @ A6
Functional Gradient Boosting based on Residual Network Perception
In Statistical Learning Theory 4
Atsushi Nitanda · Taiji Suzuki
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:40 AM -- 07:50 AM (PDT) @ A3
Fitting New Speakers Based on a Short Untranscribed Sample
In Natural Language and Speech Processing 1
Eliya Nachmani · Adam Polyak · Yaniv Taigman · Lior Wolf
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:40 AM -- 07:50 AM (PDT) @ A4
Scalable approximate Bayesian inference for particle tracking data
In Deep Learning (Bayesian) 2
Ruoxi Sun · Department of Statistics Liam Paninski
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:40 AM -- 07:50 AM (PDT) @ K11
Constrained Interacting Submodular Groupings
In Optimization (Combinatorial) 3
Andrew Cotter · Mahdi Milani Fard · Seungil You · Maya Gupta · Jeff Bilmes
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:40 AM -- 07:50 AM (PDT) @ A1
Policy and Value Transfer in Lifelong Reinforcement Learning
In Reinforcement Learning 11
David Abel · Yuu Jinnai · Sophie Guo · George Konidaris · Michael L. Littman
[ PDF] 
Oral
Thu Jul 12 07:40 AM -- 07:50 AM (PDT) @ K1
Learning Dynamics of Linear Denoising Autoencoders
In Deep Learning (Theory) 5
Arnu Pretorius · Steve Kroon · Herman Kamper
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:40 AM -- 07:50 AM (PDT) @ Victoria
Extracting Automata from Recurrent Neural Networks Using Queries and Counterexamples
In Deep Learning (Neural Network Architectures) 9
Gail Weiss · Yoav Goldberg · Eran Yahav
[ PDF] 
Oral
Thu Jul 12 07:40 AM -- 07:50 AM (PDT) @ A9
prDeep: Robust Phase Retrieval with a Flexible Deep Network
In Optimization (Non-convex) 3
Christopher Metzler · Phillip Schniter · Ashok Veeraraghavan · Richard Baraniuk
[ PDF] 
Oral
Thu Jul 12 07:50 AM -- 08:00 AM (PDT) @ A9
Accelerating Natural Gradient with Higher-Order Invariance
In Optimization (Non-convex) 3
Yang Song · Jiaming Song · Stefano Ermon
[ PDF] 
Oral
Thu Jul 12 07:50 AM -- 08:00 AM (PDT) @ A5
Stochastic Proximal Algorithms for AUC Maximization
In Online Learning 2
Michael Natole Jr · Yiming Ying · Siwei Lyu
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:50 AM -- 08:00 AM (PDT) @ A3
Towards Binary-Valued Gates for Robust LSTM Training
In Natural Language and Speech Processing 1
Zhuohan Li · Di He · Fei Tian · Wei Chen · Tao Qin · Liwei Wang · Tie-Yan Liu
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:50 AM -- 08:00 AM (PDT) @ A1
Importance Weighted Transfer of Samples in Reinforcement Learning
In Reinforcement Learning 11
Andrea Tirinzoni · Andrea Sessa · Matteo Pirotta · Marcello Restelli
[ PDF] 
Oral
Thu Jul 12 07:50 AM -- 08:00 AM (PDT) @ Victoria
High Performance Zero-Memory Overhead Direct Convolutions
In Deep Learning (Neural Network Architectures) 9
Jiyuan Zhang · Franz Franchetti · Tze Meng Low
[ PDF] 
Oral
Thu Jul 12 07:50 AM -- 08:00 AM (PDT) @ A6
Binary Classification with Karmic, Threshold-Quasi-Concave Metrics
In Statistical Learning Theory 4
Bowei Yan · Sanmi Koyejo · Kai Zhong · Pradeep Ravikumar
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:50 AM -- 08:00 AM (PDT) @ A7
LaVAN: Localized and Visible Adversarial Noise
In Deep Learning (Adversarial) 4
Danny Karmon · Daniel Zoran · Yoav Goldberg
[ PDF] 
Oral
Thu Jul 12 07:50 AM -- 08:00 AM (PDT) @ K1
Understanding Generalization and Optimization Performance of Deep CNNs
In Deep Learning (Theory) 5
Pan Zhou · Jiashi Feng
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:50 AM -- 08:00 AM (PDT) @ A4
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam
In Deep Learning (Bayesian) 2
Mohammad Emtiyaz Khan · Didrik Nielsen · Voot Tangkaratt · Wu Lin · Yarin Gal · Akash Srivastava
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:50 AM -- 08:00 AM (PDT) @ K11
Fast Maximization of Non-Submodular, Monotonic Functions on the Integer Lattice
In Optimization (Combinatorial) 3
Alan Kuhnle · J. Smith · Victoria Crawford · My T. Thai
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:00 AM -- 08:20 AM (PDT) @ A5
Let’s be Honest: An Optimal No-Regret Framework for Zero-Sum Games
In Online Learning 3
Ehsan Asadi Kangarshahi · Ya-Ping Hsieh · Mehmet Fatih Sahin · Volkan Cevher
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:00 AM -- 08:20 AM (PDT) @ K11
Representation Tradeoffs for Hyperbolic Embeddings
In Dimensionality Reduction 2
Frederic Sala · Christopher De Sa · Albert Gu · Christopher Re
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:00 AM -- 08:20 AM (PDT) @ A4
Neural Autoregressive Flows
In Deep Learning (Bayesian) 3
Chin-Wei Huang · David Krueger · Alexandre Lacoste · Aaron Courville
[ PDF] 
Oral
Thu Jul 12 08:00 AM -- 08:20 AM (PDT) @ A3
Efficient Model-Based Deep Reinforcement Learning with Variational State Tabulation
In Reinforcement Learning 13
Dane Corneil · Wulfram Gerstner · Johanni Brea
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:00 AM -- 08:20 AM (PDT) @ A1
An Efficient, Generalized Bellman Update For Cooperative Inverse Reinforcement Learning
In Reinforcement Learning 12
Dhruv Malik · Malayandi Palaniappan · Jaime Fisac · Dylan Hadfield-Menell · Stuart Russell · Anca Dragan
[ PDF] 
Oral
Thu Jul 12 08:00 AM -- 08:20 AM (PDT) @ K1
Composable Planning with Attributes
In Transfer and Multi-Task Learning 2
Amy Zhang · Sainbayar Sukhbaatar · Adam Lerer · Arthur Szlam · Facebook Rob Fergus
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:00 AM -- 08:20 AM (PDT) @ A9
Stochastic Wasserstein Barycenters
In Optimization (Non-convex) 4
Sebastian Claici · Edward Chien · Justin Solomon
[ PDF] 
Oral
Thu Jul 12 08:00 AM -- 08:20 AM (PDT) @ A6
SAFFRON: an Adaptive Algorithm for Online Control of the False Discovery Rate
In Other Models and Methods 1
Aaditya Ramdas · Tijana Zrnic · Martin Wainwright · Michael Jordan
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:00 AM -- 08:20 AM (PDT) @ Victoria
ContextNet: Deep learning for Star Galaxy Classification
In Deep Learning (Neural Network Architectures) 10
Noble Kennamer · University of California David Kirkby · Alexander Ihler · University of California Francisco Javier Sanchez-Lopez
[ PDF] 
Oral
Thu Jul 12 08:00 AM -- 08:20 AM (PDT) @ A7
Synthesizing Programs for Images using Reinforced Adversarial Learning
In Deep Learning (Adversarial) 5
Iaroslav Ganin · Tejas Kulkarni · Igor Babuschkin · S. M. Ali Eslami · Oriol Vinyals
[ PDF] 
Oral
Thu Jul 12 08:20 AM -- 08:30 AM (PDT) @ A9
Learning Compact Neural Networks with Regularization
In Optimization (Non-convex) 4
Samet Oymak
[ PDF] 
Oral
Thu Jul 12 08:20 AM -- 08:30 AM (PDT) @ A4
Distilling the Posterior in Bayesian Neural Networks
In Deep Learning (Bayesian) 3
Kuan-Chieh Wang · Paul Vicol · James Lucas · Li Gu · Roger Grosse · Richard Zemel
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:20 AM -- 08:40 AM (PDT) @ K1
Measuring abstract reasoning in neural networks
In Transfer and Multi-Task Learning 2
Adam Santoro · Feilx Hill · David GT Barrett · Ari S Morcos · Timothy Lillicrap
[ PDF]  [ PDF]  [ Video] 
Oral
Thu Jul 12 08:20 AM -- 08:30 AM (PDT) @ A5
Weakly Consistent Optimal Pricing Algorithms in Repeated Posted-Price Auctions with Strategic Buyer
In Online Learning 3
Alexey Drutsa
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:20 AM -- 08:30 AM (PDT) @ A1
Fast Bellman Updates for Robust MDPs
In Reinforcement Learning 12
Chin Pang Ho · Marek Petrik · Wolfram Wiesemann
[ PDF] 
Oral
Thu Jul 12 08:20 AM -- 08:30 AM (PDT) @ A6
Open Category Detection with PAC Guarantees
In Other Models and Methods 1
Si Liu · Risheek Garrepalli · Thomas Dietterich · Alan Fern · Dan Hendrycks
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:20 AM -- 08:40 AM (PDT) @ K11
Massively Parallel Algorithms and Hardness for Single-Linkage Clustering under $\ell_p$ Distances
In Dimensionality Reduction 2
Grigory Yaroslavtsev · Adithya Vadapalli
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:20 AM -- 08:30 AM (PDT) @ A7
MAGAN: Aligning Biological Manifolds
In Deep Learning (Adversarial) 5
Matt Amodio · Smita Krishnaswamy
[ PDF] 
Oral
Thu Jul 12 08:20 AM -- 08:40 AM (PDT) @ A3
Deep Variational Reinforcement Learning for POMDPs
In Reinforcement Learning 13
Maximilian Igl · Luisa Zintgraf · Tuan Anh Le · Frank Wood · Shimon Whiteson
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:20 AM -- 08:30 AM (PDT) @ Victoria
Autoregressive Convolutional Neural Networks for Asynchronous Time Series
In Deep Learning (Neural Network Architectures) 10
Mikolaj Binkowski · Gautier Marti · Philippe Donnat
[ PDF] 
Oral
Thu Jul 12 08:30 AM -- 08:40 AM (PDT) @ A6
Unbiased Objective Estimation in Predictive Optimization
In Other Models and Methods 1
Shinji Ito · Akihiro Yabe · Ryohei Fujimaki
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:30 AM -- 08:40 AM (PDT) @ A5
Self-Bounded Prediction Suffix Tree via Approximate String Matching
In Online Learning 3
Dongwoo Kim · Christian Walder
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:30 AM -- 08:40 AM (PDT) @ A4
Bayesian Uncertainty Estimation for Batch Normalized Deep Networks
In Deep Learning (Bayesian) 3
Mattias Teye · Hossein Azizpour · Kevin Smith
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:30 AM -- 08:40 AM (PDT) @ A1
Decoupling Gradient-Like Learning Rules from Representations
In Reinforcement Learning 12
Philip Thomas · Christoph Dann · Emma Brunskill
[ PDF] 
Oral
Thu Jul 12 08:30 AM -- 08:40 AM (PDT) @ Victoria
Hierarchical Multi-Label Classification Networks
In Deep Learning (Neural Network Architectures) 10
Jonatas Wehrmann · Ricardo Cerri · Rodrigo Barros
[ PDF] 
Oral
Thu Jul 12 08:30 AM -- 08:40 AM (PDT) @ A7
Max-Mahalanobis Linear Discriminant Analysis Networks
In Deep Learning (Adversarial) 5
Tianyu Pang · Chao Du · Jun Zhu
[ PDF] 
Oral
Thu Jul 12 08:30 AM -- 08:40 AM (PDT) @ A9
Riemannian Stochastic Recursive Gradient Algorithm with Retraction and Vector Transport and Its Convergence Analysis
In Optimization (Non-convex) 4
Hiroyuki Kasai · Hiroyuki Sato · Bamdev Mishra
[ PDF] 
Oral
Thu Jul 12 08:40 AM -- 08:50 AM (PDT) @ A7
Adversarial Time-to-Event Modeling
In Deep Learning (Adversarial) 5
Paidamoyo Chapfuwa · Chenyang Tao · Chunyuan Li · Courtney Page · Benjamin Goldstein · Lawrence Carin · Ricardo Henao
[ PDF] 
Oral
Thu Jul 12 08:40 AM -- 08:50 AM (PDT) @ A3
Recurrent Predictive State Policy Networks
In Reinforcement Learning 13
Ahmed Hefny · Zita Marinho · Wen Sun · Siddhartha Srinivasa · Geoff Gordon
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:40 AM -- 08:50 AM (PDT) @ A6
Goodness-of-fit Testing for Discrete Distributions via Stein Discrepancy
In Other Models and Methods 1
Jiasen Yang · Qiang Liu · Vinayak A Rao · Jennifer Neville
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:40 AM -- 08:50 AM (PDT) @ A4
Noisy Natural Gradient as Variational Inference
In Deep Learning (Bayesian) 3
Guodong Zhang · Shengyang Sun · David Duvenaud · Roger Grosse
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:40 AM -- 08:50 AM (PDT) @ A1
PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos
In Reinforcement Learning 12
Paavo Parmas · Carl E Rasmussen · Jan Peters · Kenji Doya
[ PDF] 
Oral
Thu Jul 12 08:40 AM -- 08:50 AM (PDT) @ A9
Low-Rank Riemannian Optimization on Positive Semidefinite Stochastic Matrices with Applications to Graph Clustering
In Optimization (Non-convex) 4
Ahmed Douik · Babak Hassibi
[ PDF] 
Oral
Thu Jul 12 08:40 AM -- 08:50 AM (PDT) @ K11
Local Density Estimation in High Dimensions
In Dimensionality Reduction 2
Xian Wu · Moses Charikar · Vishnu Natchu
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:40 AM -- 08:50 AM (PDT) @ A5
Spatio-temporal Bayesian On-line Changepoint Detection with Model Selection
In Online Learning 3
Jeremias Knoblauch · Theodoros Damoulas
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:40 AM -- 08:50 AM (PDT) @ Victoria
Nonparametric variable importance using an augmented neural network with multi-task learning
In Deep Learning (Neural Network Architectures) 10
Jean Feng · Brian Williamson · Noah Simon · Marco Carone
[ PDF] 
Oral
Thu Jul 12 08:40 AM -- 08:50 AM (PDT) @ K1
GradNorm: Gradient Normalization for Adaptive Loss Balancing in Deep Multitask Networks
In Transfer and Multi-Task Learning 2
Zhao Chen · Vijay Badrinarayanan · Chen-Yu Lee · Andrew Rabinovich
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:50 AM -- 09:00 AM (PDT) @ Victoria
Knowledge Transfer with Jacobian Matching
In Deep Learning (Neural Network Architectures) 10
Suraj Srinivas · Francois Fleuret
[ PDF] 
Oral
Thu Jul 12 08:50 AM -- 09:00 AM (PDT) @ A9
Graphical Nonconvex Optimization via an Adaptive Convex Relaxation
In Optimization (Non-convex) 4
Qiang Sun · Kean Ming Tan · Han Liu · Tong Zhang
[ PDF] 
Oral
Thu Jul 12 08:50 AM -- 09:00 AM (PDT) @ A7
Reinforcing Adversarial Robustness using Model Confidence Induced by Adversarial Training
In Deep Learning (Adversarial) 5
Xi Wu · Wooyeong Jang · Jiefeng Chen · Lingjiao Chen · Somesh Jha
[ PDF] 
Oral
Thu Jul 12 08:50 AM -- 09:00 AM (PDT) @ A5
Learning Localized Spatio-Temporal Models From Streaming Data
In Online Learning 3
Muhammad Osama · Dave Zachariah · Thomas Schön
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:50 AM -- 09:00 AM (PDT) @ K11
Improving Sign Random Projections With Additional Information
In Dimensionality Reduction 2
Keegan Kang · Wei Pin Wong
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:50 AM -- 09:00 AM (PDT) @ A4
Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors
In Deep Learning (Bayesian) 3
Soumya Ghosh · Jiayu Yao · Finale Doshi-Velez
[ PDF] 
Oral
Thu Jul 12 08:50 AM -- 09:00 AM (PDT) @ A3
Regret Minimization for Partially Observable Deep Reinforcement Learning
In Reinforcement Learning 13
Peter Jin · EECS Kurt Keutzer · Sergey Levine
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:50 AM -- 09:00 AM (PDT) @ A1
Discovering and Removing Exogenous State Variables and Rewards for Reinforcement Learning
In Reinforcement Learning 12
Thomas Dietterich · George Trimponias · Zhitang Chen
[ PDF] 
Oral
Thu Jul 12 08:50 AM -- 09:00 AM (PDT) @ A6
Towards Black-box Iterative Machine Teaching
In Other Models and Methods 1
Weiyang Liu · Bo Dai · Xingguo Li · Zhen Liu · James Rehg · Le Song
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:50 AM -- 09:00 AM (PDT) @ K1
Explicit Inductive Bias for Transfer Learning with Convolutional Networks
In Transfer and Multi-Task Learning 2
Xuhong LI · Yves Grandvalet · Franck Davoine
[ PDF]  [ Video] 
Oral
Fri Jul 13 12:30 AM -- 12:50 AM (PDT) @ K11
Out-of-sample extension of graph adjacency spectral embedding
In Dimensionality Reduction 3
Keith Levin · Fred Roosta · Michael Mahoney · Carey Priebe
[ PDF]  [ Video] 
Oral
Fri Jul 13 12:30 AM -- 12:50 AM (PDT) @ A1
RLlib: Abstractions for Distributed Reinforcement Learning
In Reinforcement Learning 14
Eric Liang · Richard Liaw · Robert Nishihara · Philipp Moritz · Roy Fox · Ken Goldberg · Joseph E Gonzalez · Michael Jordan · Ion Stoica
[ PDF] 
Oral
Fri Jul 13 12:30 AM -- 12:50 AM (PDT) @ A6
A Reductions Approach to Fair Classification
In Society Impacts of Machine Learning 2
Alekh Agarwal · Alina Beygelzimer · Miroslav Dudik · John Langford · Hanna Wallach
[ PDF]  [ Video] 
Oral
Fri Jul 13 12:30 AM -- 12:50 AM (PDT) @ A4
Learning in Integer Latent Variable Models with Nested Automatic Differentiation
In Graphical Models 2
Daniel Sheldon · Kevin Winner · Debora Sujono
[ PDF] 
Oral
Fri Jul 13 12:30 AM -- 12:50 AM (PDT) @ A9
Convergence guarantees for a class of non-convex and non-smooth optimization problems
In Optimization (Non-convex) 5
Koulik Khamaru · Martin Wainwright
[ PDF] 
Oral
Fri Jul 13 12:30 AM -- 12:50 AM (PDT) @ Victoria
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV)
In Other Models and Methods 2
Been Kim · Martin Wattenberg · Justin Gilmer · Carrie Cai · James Wexler · Fernanda Viégas · Rory sayres
[ PDF] 
Oral
Fri Jul 13 12:30 AM -- 12:50 AM (PDT) @ K1
Solving Partial Assignment Problems using Random Clique Complexes
In Computer Vision 2
Charu Sharma · Deepak Nathani · Manu Kaul
[ PDF]  [ Video] 
Oral
Fri Jul 13 12:30 AM -- 12:50 AM (PDT) @ A7
Mixed batches and symmetric discriminators for GAN training
In Deep Learning (Adversarial) 6
Thomas LUCAS · Corentin Tallec · Yann Ollivier · Jakob Verbeek
[ PDF]  [ Video] 
Oral
Fri Jul 13 12:30 AM -- 12:50 AM (PDT) @ A3
Learning Registered Point Processes from Idiosyncratic Observations
In Time-Series Analysis 1
Hongteng Xu · Lawrence Carin · Hongyuan Zha
[ PDF] 
Oral
Fri Jul 13 12:30 AM -- 12:50 AM (PDT) @ A5
Dynamic Regret of Strongly Adaptive Methods
In Online Learning 4
Lijun Zhang · Tianbao Yang · rong jin · Zhi-Hua Zhou
[ PDF]  [ Video] 
Oral
Fri Jul 13 12:50 AM -- 01:00 AM (PDT) @ K1
Generalized Earley Parser: Bridging Symbolic Grammars and Sequence Data for Future Prediction
In Computer Vision 2
Siyuan Qi · Baoxiong Jia · Song-Chun Zhu
[ PDF]  [ Video] 
Oral
Fri Jul 13 12:50 AM -- 01:10 AM (PDT) @ A9
A Progressive Batching L-BFGS Method for Machine Learning
In Optimization (Non-convex) 5
Vijaya Raghavendra Bollapragada · Jorge Nocedal · Dheevatsa Mudigere · Hao-Jun M Shi · Peter Tang
[ PDF] 
Oral
Fri Jul 13 12:50 AM -- 01:10 AM (PDT) @ A6
Probably Approximately Metric-Fair Learning
In Society Impacts of Machine Learning 2
Gal Yona · Guy Rothblum
[ PDF]  [ Video] 
Oral
Fri Jul 13 12:50 AM -- 01:00 AM (PDT) @ A7
Mutual Information Neural Estimation
In Deep Learning (Adversarial) 6
Mohamed Belghazi · Aristide Baratin · Sai Rajeswar · Sherjil Ozair · Yoshua Bengio · R Devon Hjelm · Aaron Courville
[ PDF]  [ Video] 
Oral
Fri Jul 13 12:50 AM -- 01:00 AM (PDT) @ Victoria
Learning equations for extrapolation and control
In Other Models and Methods 2
Subham S Sahoo · Christoph H. Lampert · Georg Martius
[ PDF] 
Oral
Fri Jul 13 12:50 AM -- 01:00 AM (PDT) @ K11
Bayesian Model Selection for Change Point Detection and Clustering
In Dimensionality Reduction 3
othmane mazhar · Cristian R. Rojas · Inst. of Technology Carlo Fischione · Mohammad Reza Hesamzadeh
[ PDF]  [ Video] 
Oral
Fri Jul 13 12:50 AM -- 01:10 AM (PDT) @ A1
IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures
In Reinforcement Learning 14
Lasse Espeholt · Hubert Soyer · Remi Munos · Karen Simonyan · Vlad Mnih · Tom Ward · Yotam Doron · Vlad Firoiu · Tim Harley · Iain Dunning · Shane Legg · Koray Kavukcuoglu
[ PDF] 
Oral
Fri Jul 13 12:50 AM -- 01:00 AM (PDT) @ A5
Online Learning with Abstention
In Online Learning 4
Corinna Cortes · Giulia DeSalvo · Claudio Gentile · Mehryar Mohri · Scott Yang
[ PDF]  [ Video] 
Oral
Fri Jul 13 12:50 AM -- 01:00 AM (PDT) @ A4
Sound Abstraction and Decomposition of Probabilistic Programs
In Graphical Models 2
Steven Holtzen · Guy Van den Broeck · Todd Millstein
[ PDF] 
Oral
Fri Jul 13 12:50 AM -- 01:10 AM (PDT) @ A3
Deep Bayesian Nonparametric Tracking
In Time-Series Analysis 1
Aonan Zhang · John Paisley
[ PDF] 
Oral
Fri Jul 13 01:00 AM -- 01:10 AM (PDT) @ Victoria
PDE-Net: Learning PDEs from Data
In Other Models and Methods 2
Zichao Long · Yiping Lu · Xianzhong Ma · Bin Dong
[ PDF] 
Oral
Fri Jul 13 01:00 AM -- 01:10 AM (PDT) @ K1
Video Prediction with Appearance and Motion Conditions
In Computer Vision 2
Yunseok Jang · Gunhee Kim · Yale Song
[ PDF]  [ Video] 
Oral
Fri Jul 13 01:00 AM -- 01:10 AM (PDT) @ A5
Multi-Fidelity Black-Box Optimization with Hierarchical Partitions
In Online Learning 4
Rajat Sen · kirthevasan kandasamy · Sanjay Shakkottai
[ PDF]  [ Video] 
Oral
Fri Jul 13 01:00 AM -- 01:10 AM (PDT) @ K11
An Iterative, Sketching-based Framework for Ridge Regression
In Dimensionality Reduction 3
Agniva Chowdhury · Jiasen Yang · Petros Drineas
[ PDF]  [ Video] 
Oral
Fri Jul 13 01:00 AM -- 01:10 AM (PDT) @ A7
Adversarially Regularized Autoencoders
In Deep Learning (Adversarial) 6
Jake Zhao · Yoon Kim · Kelly Zhang · Alexander Rush · Yann LeCun
[ PDF]  [ Video] 
Oral
Fri Jul 13 01:00 AM -- 01:10 AM (PDT) @ A4
Parallel Bayesian Network Structure Learning
In Graphical Models 2
Tian Gao · Dennis Wei
[ PDF] 
Oral
Fri Jul 13 01:10 AM -- 01:20 AM (PDT) @ A1
Mix & Match - Agent Curricula for Reinforcement Learning
In Reinforcement Learning 14
Wojciech Czarnecki · Siddhant Jayakumar · Max Jaderberg · Leonard Hasenclever · Yee Teh · Nicolas Heess · Simon Osindero · Razvan Pascanu
[ PDF] 
Oral
Fri Jul 13 01:10 AM -- 01:20 AM (PDT) @ Victoria
Transformation Autoregressive Networks
In Other Models and Methods 2
Junier Oliva · Kumar Avinava Dubey · Manzil Zaheer · Barnabás Póczos · Ruslan Salakhutdinov · Eric Xing · Jeff Schneider
[ PDF] 
Oral
Fri Jul 13 01:10 AM -- 01:20 AM (PDT) @ A4
The Edge Density Barrier: Computational-Statistical Tradeoffs in Combinatorial Inference
In Graphical Models 2
Hao Lu · Yuan Cao · Junwei Lu · Han Liu · Zhaoran Wang
[ PDF] 
Oral
Fri Jul 13 01:10 AM -- 01:20 AM (PDT) @ K11
Provable Variable Selection for Streaming Features
In Dimensionality Reduction 3
Jing Wang · Jie Shen · Ping Li
[ PDF]  [ Video] 
Oral
Fri Jul 13 01:10 AM -- 01:20 AM (PDT) @ A7
JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets
In Deep Learning (Adversarial) 6
Yunchen Pu · Shuyang Dai · Zhe Gan · Weiyao Wang · Guoyin Wang · Yizhe Zhang · Ricardo Henao · Lawrence Carin
[ PDF]  [ Video] 
Oral
Fri Jul 13 01:10 AM -- 01:20 AM (PDT) @ K1
Neural Program Synthesis from Diverse Demonstration Videos
In Computer Vision 2
Shao-Hua Sun · Hyeonwoo Noh · Sriram Somasundaram · Joseph Lim
[ PDF]  [ Video] 
Oral
Fri Jul 13 01:10 AM -- 01:20 AM (PDT) @ A6
Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness
In Society Impacts of Machine Learning 2
Michael Kearns · Seth Neel · Aaron Roth · Steven Wu
[ PDF] 
Oral
Fri Jul 13 01:10 AM -- 01:20 AM (PDT) @ A3
Learning Hidden Markov Models from Pairwise Co-occurrences with Application to Topic Modeling
In Time-Series Analysis 1
Kejun Huang · Xiao Fu · Nicholas Sidiropoulos
[ PDF] 
Oral
Fri Jul 13 01:10 AM -- 01:20 AM (PDT) @ A5
Adaptive Exploration-Exploitation Tradeoff for Opportunistic Bandits
In Online Learning 4
Huasen Wu · Xueying Guo · Xin Liu
[ PDF]  [ Video] 
Oral
Fri Jul 13 01:10 AM -- 01:20 AM (PDT) @ A9
Gradient Primal-Dual Algorithm Converges to Second-Order Stationary Solution for Nonconvex Distributed Optimization Over Networks
In Optimization (Non-convex) 5
Mingyi Hong · Meisam Razaviyayn · Jason Lee
[ PDF] 
Oral
Fri Jul 13 01:20 AM -- 01:30 AM (PDT) @ A5
Firing Bandits: Optimizing Crowdfunding
In Online Learning 4
Lalit Jain · Kevin Jamieson
[ PDF]  [ Video] 
Oral
Fri Jul 13 01:20 AM -- 01:30 AM (PDT) @ A1
Learning to Explore via Meta-Policy Gradient
In Reinforcement Learning 14
Tianbing Xu · Qiang Liu · Liang Zhao · Jian Peng
[ PDF] 
Oral
Fri Jul 13 01:20 AM -- 01:30 AM (PDT) @ K11
Learning Low-Dimensional Temporal Representations
In Dimensionality Reduction 3
Bing Su · Ying Wu
[ PDF]  [ Video] 
Oral
Fri Jul 13 01:20 AM -- 01:30 AM (PDT) @ A7
Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Data
In Deep Learning (Adversarial) 6
Amjad Almahairi · Sai Rajeswar · Alessandro Sordoni · Philip Bachman · Aaron Courville
[ PDF]  [ Video] 
Oral
Fri Jul 13 01:20 AM -- 01:30 AM (PDT) @ A4
Temporal Poisson Square Root Graphical Models
In Graphical Models 2
Sinong Geng · Zhaobin Kuang · Peggy Peissig · University of Wisconsin David Page
[ PDF] 
Oral
Fri Jul 13 01:20 AM -- 01:30 AM (PDT) @ A9
Estimation of Markov Chain via Rank-constrained Likelihood
In Optimization (Non-convex) 5
XUDONG LI · Mengdi Wang · Anru Zhang
[ PDF] 
Oral
Fri Jul 13 01:20 AM -- 01:30 AM (PDT) @ Victoria
Weightless: Lossy weight encoding for deep neural network compression
In Other Models and Methods 2
Brandon Reagen · Udit Gupta · Bob Adolf · Michael Mitzenmacher · Alexander Rush · Gu-Yeon Wei · David Brooks
[ PDF] 
Oral
Fri Jul 13 01:20 AM -- 01:30 AM (PDT) @ A6
Blind Justice: Fairness with Encrypted Sensitive Attributes
In Society Impacts of Machine Learning 2
Niki Kilbertus · Adria Gascon · Matt Kusner · Michael Veale · Krishna Gummadi · Adrian Weller
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:00 AM -- 02:20 AM (PDT) @ A3
Learning Adversarially Fair and Transferable Representations
In Transfer and Multi-Task Learning 3
David Madras · Elliot Creager · Toniann Pitassi · Richard Zemel
[ PDF] 
Oral
Fri Jul 13 02:00 AM -- 02:20 AM (PDT) @ A6
Theoretical Analysis of Sparse Subspace Clustering with Missing Entries
In Unsupervised Learning 2
Manolis Tsakiris · Rene Vidal
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:00 AM -- 02:20 AM (PDT) @ K1
Spurious Local Minima are Common in Two-Layer ReLU Neural Networks
In Deep Learning (Theory) 6
Itay Safran · Ohad Shamir
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:00 AM -- 02:20 AM (PDT) @ A9
A Conditional Gradient Framework for Composite Convex Minimization with Applications to Semidefinite Programming
In Optimization (Convex) 5
Alp Yurtsever · Olivier Fercoq · Francesco Locatello · Volkan Cevher
[ PDF] 
Oral
Fri Jul 13 02:00 AM -- 02:20 AM (PDT) @ A7
Junction Tree Variational Autoencoder for Molecular Graph Generation
In Generative Models 3
Wengong Jin · Regina Barzilay · Tommi Jaakkola
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:00 AM -- 02:20 AM (PDT) @ A4
Scalable Gaussian Processes with Grid-Structured Eigenfunctions (GP-GRIEF)
In Gaussian Processes 3
Trefor Evans · Prasanth B Nair
[ PDF] 
Oral
Fri Jul 13 02:00 AM -- 02:20 AM (PDT) @ Victoria
Efficient Neural Audio Synthesis
In Deep Learning (Neural Network Architectures) 11
Nal Kalchbrenner · Erich Elsen · Karen Simonyan · Seb Noury · Norman Casagrande · Edward Lockhart · Florian Stimberg · Aäron van den Oord · Sander Dieleman · Koray Kavukcuoglu
[ PDF] 
Oral
Fri Jul 13 02:00 AM -- 02:20 AM (PDT) @ A5
Online Linear Quadratic Control
In Online Learning 5
Alon Cohen · Avinatan Hasidim · Tomer Koren · Nevena Lazic · Yishay Mansour · Kunal Talwar
[ PDF] 
Oral
Fri Jul 13 02:00 AM -- 02:20 AM (PDT) @ A1
Hierarchical Imitation and Reinforcement Learning
In Reinforcement Learning 15
Hoang Le · Nan Jiang · Alekh Agarwal · Miroslav Dudik · Yisong Yue · Hal Daumé III
[ PDF] 
Oral
Fri Jul 13 02:00 AM -- 02:20 AM (PDT) @ K11
Competitive Caching with Machine Learned Advice
In Optimization (Combinatorial) 4
Thodoris Lykouris · Sergei Vassilvitskii
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:20 AM -- 02:30 AM (PDT) @ A6
Improved nearest neighbor search using auxiliary information and priority functions
In Unsupervised Learning 2
Omid Keivani · Kaushik Sinha
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:20 AM -- 02:40 AM (PDT) @ A1
Using Reward Machines for High-Level Task Specification and Decomposition in Reinforcement Learning
In Reinforcement Learning 15
Rodrigo A Toro Icarte · Toryn Q Klassen · Richard Valenzano · Sheila McIlraith
[ PDF] 
Oral
Fri Jul 13 02:20 AM -- 02:30 AM (PDT) @ K11
Distributed Clustering via LSH Based Data Partitioning
In Optimization (Combinatorial) 4
Aditya Bhaskara · Pruthuvi Maheshakya Wijewardena
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:20 AM -- 02:40 AM (PDT) @ A7
Semi-Amortized Variational Autoencoders
In Generative Models 3
Yoon Kim · Sam Wiseman · Andrew Miller · David Sontag · Alexander Rush
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:20 AM -- 02:40 AM (PDT) @ A5
Semiparametric Contextual Bandits
In Online Learning 5
Akshay Krishnamurthy · Steven Wu · Vasilis Syrgkanis
[ PDF] 
Oral
Fri Jul 13 02:20 AM -- 02:40 AM (PDT) @ K1
Gradient descent with identity initialization efficiently learns positive definite linear transformations by deep residual networks
In Deep Learning (Theory) 6
Peter Bartlett · Dave Helmbold · Phil Long
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:20 AM -- 02:30 AM (PDT) @ A3
Learning Semantic Representations for Unsupervised Domain Adaptation
In Transfer and Multi-Task Learning 3
Shaoan Xie · Zibin Zheng · Liang Chen · Chuan Chen
[ PDF] 
Oral
Fri Jul 13 02:20 AM -- 02:40 AM (PDT) @ A4
State Space Gaussian Processes with Non-Gaussian Likelihood
In Gaussian Processes 3
Hannes Nickisch · Arno Solin · Alexander Grigorevskiy
[ PDF] 
Oral
Fri Jul 13 02:20 AM -- 02:40 AM (PDT) @ Victoria
Understanding and Simplifying One-Shot Architecture Search
In Deep Learning (Neural Network Architectures) 11
Gabriel Bender · Pieter-Jan Kindermans · Barret Zoph · Vijay Vasudevan · Quoc Le
[ PDF] 
Oral
Fri Jul 13 02:20 AM -- 02:40 AM (PDT) @ A9
Frank-Wolfe with Subsampling Oracle
In Optimization (Convex) 5
Thomas Kerdreux · Fabian Pedregosa · Alexandre d'Aspremont
[ PDF] 
Oral
Fri Jul 13 02:30 AM -- 02:40 AM (PDT) @ K11
Learning to Branch
In Optimization (Combinatorial) 4
Nina Balcan · Travis Dick · Tuomas Sandholm · Ellen Vitercik
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:30 AM -- 02:40 AM (PDT) @ A6
QuantTree: Histograms for Change Detection in Multivariate Data Streams
In Unsupervised Learning 2
Giacomo Boracchi · Diego Carrera · Cristiano Cervellera · Danilo Macciò
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:30 AM -- 02:40 AM (PDT) @ A3
CyCADA: Cycle-Consistent Adversarial Domain Adaptation
In Transfer and Multi-Task Learning 3
Judy Hoffman · Eric Tzeng · Taesung Park · Jun-Yan Zhu · Philip Isola · Kate Saenko · Alexei Efros · Trevor Darrell
[ PDF] 
Oral
Fri Jul 13 02:40 AM -- 02:50 AM (PDT) @ A5
Minimax Concave Penalized Multi-Armed Bandit Model with High-Dimensional Covariates
In Online Learning 5
xue wang · Mingcheng Wei · Tao Yao
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:40 AM -- 02:50 AM (PDT) @ K1
On the Power of Over-parametrization in Neural Networks with Quadratic Activation
In Deep Learning (Theory) 6
Simon Du · Jason Lee
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:40 AM -- 02:50 AM (PDT) @ A6
Topological mixture estimation
In Unsupervised Learning 2
Steve Huntsman
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:40 AM -- 02:50 AM (PDT) @ A9
On Matching Pursuit and Coordinate Descent
In Optimization (Convex) 5
Francesco Locatello · Anant Raj · Sai Praneeth Reddy Karimireddy · Gunnar Ratsch · Bernhard Schölkopf · Sebastian Stich · Martin Jaggi
[ PDF] 
Oral
Fri Jul 13 02:40 AM -- 02:50 AM (PDT) @ K11
Compiling Combinatorial Prediction Games
In Optimization (Combinatorial) 4
Frederic Koriche
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:40 AM -- 02:50 AM (PDT) @ A7
Iterative Amortized Inference
In Generative Models 3
Joe Marino · Yisong Yue · Stephan Mandt
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:40 AM -- 02:50 AM (PDT) @ A1
State Abstractions for Lifelong Reinforcement Learning
In Reinforcement Learning 15
David Abel · Dilip S. Arumugam · Lucas Lehnert · Michael L. Littman
[ PDF] 
Oral
Fri Jul 13 02:40 AM -- 02:50 AM (PDT) @ Victoria
Path-Level Network Transformation for Efficient Architecture Search
In Deep Learning (Neural Network Architectures) 11
Han Cai · Jiacheng Yang · Weinan Zhang · Song Han · Yong Yu
[ PDF] 
Oral
Fri Jul 13 02:40 AM -- 02:50 AM (PDT) @ A4
Constant-Time Predictive Distributions for Gaussian Processes
In Gaussian Processes 3
Geoff Pleiss · Jacob Gardner · Kilian Weinberger · Andrew Wilson
[ PDF] 
Oral
Fri Jul 13 02:40 AM -- 02:50 AM (PDT) @ A3
Rectify Heterogeneous Models with Semantic Mapping
In Transfer and Multi-Task Learning 3
Han-Jia Ye · De-Chuan Zhan · Yuan Jiang · Zhi-Hua Zhou
[ PDF]  [ PDF] 
Oral
Fri Jul 13 02:50 AM -- 03:00 AM (PDT) @ A9
Adaptive Three Operator Splitting
In Optimization (Convex) 5
Fabian Pedregosa · Gauthier Gidel
[ PDF] 
Oral
Fri Jul 13 02:50 AM -- 03:00 AM (PDT) @ A6
Revealing Common Statistical Behaviors in Heterogeneous Populations
In Unsupervised Learning 2
Andrey Zhitnikov · Rotem Mulayoff · Tomer Michaeli
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:50 AM -- 03:00 AM (PDT) @ A7
DVAE++: Discrete Variational Autoencoders with Overlapping Transformations
In Generative Models 3
Arash Vahdat · William Macready · Zhengbing Bian · Amir Khoshaman · Evgeny Andriyash
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:50 AM -- 03:00 AM (PDT) @ A3
Detecting and Correcting for Label Shift with Black Box Predictors
In Transfer and Multi-Task Learning 3
Zachary Lipton · Yu-Xiang Wang · Alexander Smola
[ PDF] 
Oral
Fri Jul 13 02:50 AM -- 03:00 AM (PDT) @ A1
Policy Optimization with Demonstrations
In Reinforcement Learning 15
Bingyi Kang · Zequn Jie · Jiashi Feng
[ PDF] 
Oral
Fri Jul 13 02:50 AM -- 03:00 AM (PDT) @ Victoria
Learning Longer-term Dependencies in RNNs with Auxiliary Losses
In Deep Learning (Neural Network Architectures) 11
Trieu H Trinh · Andrew Dai · Thang Luong · Quoc Le
[ PDF] 
Oral
Fri Jul 13 02:50 AM -- 03:00 AM (PDT) @ K11
Approximation Algorithms for Cascading Prediction Models
In Optimization (Combinatorial) 4
Matthew Streeter
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:50 AM -- 03:00 AM (PDT) @ A4
Large-Scale Cox Process Inference using Variational Fourier Features
In Gaussian Processes 3
ST John · James Hensman
[ PDF] 
Oral
Fri Jul 13 02:50 AM -- 03:00 AM (PDT) @ K1
Optimization Landscape and Expressivity of Deep CNNs
In Deep Learning (Theory) 6
Quynh Nguyen · Matthias Hein
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:50 AM -- 03:00 AM (PDT) @ A5
Racing Thompson: an Efficient Algorithm for Thompson Sampling with Non-conjugate Priors
In Online Learning 5
Yichi Zhou · Jun Zhu · Jingwei Zhuo
[ PDF] 
Oral
Fri Jul 13 07:00 AM -- 07:20 AM (PDT) @ A7
Parallel WaveNet: Fast High-Fidelity Speech Synthesis
In Generative Models 4
Aäron van den Oord · Yazhe Li · Igor Babuschkin · Karen Simonyan · Oriol Vinyals · Koray Kavukcuoglu · George van den Driessche · Edward Lockhart · Luis C Cobo · Florian Stimberg · Norman Casagrande · Dominik Grewe · Seb Noury · Sander Dieleman · Erich Elsen · Nal Kalchbrenner · Heiga Zen · Alex Graves · Helen King · Tom Walters · Dan Belov · Demis Hassabis
[ PDF]  [ Video] 
Oral
Fri Jul 13 07:00 AM -- 07:20 AM (PDT) @ K1
Efficient end-to-end learning for quantizable representations
In Deep Learning (Theory) 7
Yeonwoo Jeong · Hyun Oh Song
[ PDF]  [ Video] 
Oral
Fri Jul 13 07:00 AM -- 07:20 AM (PDT) @ A9
SADAGRAD: Strongly Adaptive Stochastic Gradient Methods
In Optimization (Convex) 6
Zaiyi Chen · Yi Xu · Enhong Chen · Tianbao Yang
[ PDF] 
Oral
Fri Jul 13 07:00 AM -- 07:20 AM (PDT) @ A6
Candidates vs. Noises Estimation for Large Multi-Class Classification Problem
In Supervised Learning 3
Lei Han · Yiheng Huang · Tong Zhang
[ PDF]  [ Video] 
Oral
Fri Jul 13 07:00 AM -- 07:20 AM (PDT) @ A3
The Hidden Vulnerability of Distributed Learning in Byzantium
In Parallel and Distributed Learning 3
El Mahdi El Mhamdi · Rachid Guerraoui · Sébastien Rouault
[ PDF] 
Oral
Fri Jul 13 07:00 AM -- 07:20 AM (PDT) @ A4
Stein Variational Gradient Descent Without Gradient
In Monte Carlo Methods 2
Jun Han · Qiang Liu
[ PDF] 
Oral
Fri Jul 13 07:00 AM -- 07:20 AM (PDT) @ K11
On the Spectrum of Random Features Maps of High Dimensional Data
In Spectral Methods 1
Zhenyu Liao · Romain Couillet
[ PDF]  [ Video] 
Oral
Fri Jul 13 07:00 AM -- 07:20 AM (PDT) @ A1
Global Convergence of Policy Gradient Methods for the Linear Quadratic Regulator
In Reinforcement Learning 16
Maryam Fazel · Rong Ge · Sham Kakade · Mehran Mesbahi
[ PDF] 
Oral
Fri Jul 13 07:00 AM -- 07:20 AM (PDT) @ Victoria
Progress & Compress: A scalable framework for continual learning
In Deep Learning (Neural Network Architectures) 12
Jonathan Schwarz · Wojciech Czarnecki · Jelena Luketina · Agnieszka Grabska-Barwinska · Yee Teh · Razvan Pascanu · Raia Hadsell
[ PDF] 
Oral
Fri Jul 13 07:00 AM -- 07:20 AM (PDT) @ A5
Causal Bandits with Propagating Inference
In Causal Inference 1
Akihiro Yabe · Daisuke Hatano · Hanna Sumita · Shinji Ito · Naonori Kakimura · Takuro Fukunaga · Ken-ichi Kawarabayashi
[ PDF] 
Oral
Fri Jul 13 07:20 AM -- 07:30 AM (PDT) @ A9
Level-Set Methods for Finite-Sum Constrained Convex Optimization
In Optimization (Convex) 6
Qihang Lin · Runchao Ma · Tianbao Yang
[ PDF] 
Oral
Fri Jul 13 07:20 AM -- 07:40 AM (PDT) @ A7
Autoregressive Quantile Networks for Generative Modeling
In Generative Models 4
Georg Ostrovski · Will Dabney · Remi Munos
[ PDF]  [ Video] 
Oral
Fri Jul 13 07:20 AM -- 07:30 AM (PDT) @ A6
CRAFTML, an Efficient Clustering-based Random Forest for Extreme Multi-label Learning
In Supervised Learning 3
Wissam Siblini · Frank Meyer · Pascale Kuntz
[ PDF]  [ Video] 
Oral
Fri Jul 13 07:20 AM -- 07:40 AM (PDT) @ A3
Asynchronous Byzantine Machine Learning (the case of SGD)
In Parallel and Distributed Learning 3
Georgios Damaskinos · El Mahdi El Mhamdi · Rachid Guerraoui · Rhicheek Patra · Mahsa Taziki
[ PDF] 
Oral
Fri Jul 13 07:20 AM -- 07:40 AM (PDT) @ Victoria
Overcoming Catastrophic Forgetting with Hard Attention to the Task
In Deep Learning (Neural Network Architectures) 12
Joan Serrà · Didac Suris · Marius Miron · Alexandros Karatzoglou
[ PDF] 
Oral
Fri Jul 13 07:20 AM -- 07:40 AM (PDT) @ A5
Characterizing and Learning Equivalence Classes of Causal DAGs under Interventions
In Causal Inference 1
Karren Yang · Abigail Katoff · Caroline Uhler
[ PDF] 
Oral
Fri Jul 13 07:20 AM -- 07:40 AM (PDT) @ A4
Minibatch Gibbs Sampling on Large Graphical Models
In Monte Carlo Methods 2
Christopher De Sa · Vincent Chen · Wong
[ PDF]  [ PDF] 
Oral
Fri Jul 13 07:20 AM -- 07:30 AM (PDT) @ K1
High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach
In Deep Learning (Theory) 7
Tim Pearce · Alexandra Brintrup · Mohamed Zaki · Andy Neely
[ PDF]  [ Video] 
Oral
Fri Jul 13 07:20 AM -- 07:30 AM (PDT) @ A1
Policy Optimization as Wasserstein Gradient Flows
In Reinforcement Learning 16
RUIYI (ROY) ZHANG · Changyou Chen · Chunyuan Li · Lawrence Carin
[ PDF] 
Oral
Fri Jul 13 07:20 AM -- 07:30 AM (PDT) @ K11
SMAC: Simultaneous Mapping and Clustering Using Spectral Decompositions
In Spectral Methods 1
chandrajit bajaj · Tingran Gao · Zihang He · Qixing Huang · Zhenxiao Liang
[ PDF]  [ Video] 
Oral
Fri Jul 13 07:30 AM -- 07:40 AM (PDT) @ A6
Attention-based Deep Multiple Instance Learning
In Supervised Learning 3
Maximilian Ilse · Jakub Tomczak · Max Welling
[ PDF]  [ Video] 
Oral
Fri Jul 13 07:30 AM -- 07:40 AM (PDT) @ A9
Local Convergence Properties of SAGA/Prox-SVRG and Acceleration
In Optimization (Convex) 6
Clarice Poon · Jingwei Liang · Carola-Bibiane Schönlieb
[ PDF] 
Oral
Fri Jul 13 07:30 AM -- 07:40 AM (PDT) @ A1
Clipped Action Policy Gradient
In Reinforcement Learning 16
Yasuhiro Fujita · Shin-ichi Maeda
[ PDF] 
Oral
Fri Jul 13 07:30 AM -- 07:40 AM (PDT) @ K1
A Boo(n) for Evaluating Architecture Performance
In Deep Learning (Theory) 7
Ondrej Bajgar · Rudolf Kadlec · Jan Kleindienst
[ PDF]  [ Video] 
Oral
Fri Jul 13 07:30 AM -- 07:40 AM (PDT) @ K11
Spectrally Approximating Large Graphs with Smaller Graphs
In Spectral Methods 1
Andreas Loukas · Pierre Vandergheynst
[ PDF]  [ Video] 
Oral
Fri Jul 13 07:40 AM -- 07:50 AM (PDT) @ K11
Submodular Hypergraphs: p-Laplacians, Cheeger Inequalities and Spectral Clustering
In Spectral Methods 1
Pan Li · Olgica Milenkovic
[ PDF]  [ Video] 
Oral
Fri Jul 13 07:40 AM -- 07:50 AM (PDT) @ A1
Fourier Policy Gradients
In Reinforcement Learning 16
Matthew Fellows · Kamil Ciosek · Shimon Whiteson
[ PDF] 
Oral
Fri Jul 13 07:40 AM -- 07:50 AM (PDT) @ A4
On Nesting Monte Carlo Estimators
In Monte Carlo Methods 2
Tom Rainforth · Rob Cornish · Hongseok Yang · andrew warrington · Frank Wood
[ PDF] 
Oral
Fri Jul 13 07:40 AM -- 07:50 AM (PDT) @ Victoria
Rapid Adaptation with Conditionally Shifted Neurons
In Deep Learning (Neural Network Architectures) 12
Tsendsuren Munkhdalai · Xingdi Yuan · Soroush Mehri · Adam Trischler
[ PDF] 
Oral
Fri Jul 13 07:40 AM -- 07:50 AM (PDT) @ A9
Continuous and Discrete-time Accelerated Stochastic Mirror Descent for Strongly Convex Functions
In Optimization (Convex) 6
Pan Xu · Tianhao Wang · Quanquan Gu
[ PDF] 
Oral
Fri Jul 13 07:40 AM -- 07:50 AM (PDT) @ A5
Budgeted Experiment Design for Causal Structure Learning
In Causal Inference 1
AmirEmad Ghassami · Saber Salehkaleybar · Negar Kiyavash · Elias Bareinboim
[ PDF] 
Oral
Fri Jul 13 07:40 AM -- 07:50 AM (PDT) @ K1
Entropy-SGD optimizes the prior of a PAC-Bayes bound: Generalization properties of Entropy-SGD and data-dependent priors
In Deep Learning (Theory) 7
Gintare Karolina Dziugaite · Daniel Roy
[ PDF] 
Oral
Fri Jul 13 07:40 AM -- 07:50 AM (PDT) @ A7
Stochastic Video Generation with a Learned Prior
In Generative Models 4
Emily Denton · Rob Fergus
[ PDF]  [ Video] 
Oral
Fri Jul 13 07:40 AM -- 07:50 AM (PDT) @ A3
DRACO: Byzantine-resilient Distributed Training via Redundant Gradients
In Parallel and Distributed Learning 3
Lingjiao Chen · Hongyi Wang · Zachary Charles · Dimitris Papailiopoulos
[ PDF] 
Oral
Fri Jul 13 07:40 AM -- 07:50 AM (PDT) @ A6
Learning and Memorization
In Supervised Learning 3
Sat Chatterjee
[ PDF]  [ Video] 
Oral
Fri Jul 13 07:50 AM -- 08:00 AM (PDT) @ A6
Trainable Calibration Measures for Neural Networks from Kernel Mean Embeddings
In Supervised Learning 3
Aviral Kumar · Sunita Sarawagi · Ujjwal Jain
[ PDF]  [ Video] 
Oral
Fri Jul 13 07:50 AM -- 08:00 AM (PDT) @ A9
Fast Gradient-Based Methods with Exponential Rate: A Hybrid Control Framework
In Optimization (Convex) 6
Arman Sharifi Kolarijani · Peyman Mohajerin Esfahani · Tamas Keviczky
[ PDF] 
Oral
Fri Jul 13 07:50 AM -- 08:00 AM (PDT) @ A5
The Hierarchical Adaptive Forgetting Variational Filter
In Causal Inference 1
Vincent Moens
[ PDF] 
Oral
Fri Jul 13 07:50 AM -- 08:00 AM (PDT) @ A4
On the Theory of Variance Reduction for Stochastic Gradient Monte Carlo
In Monte Carlo Methods 2
Niladri Chatterji · Nicolas Flammarion · Yian Ma · Peter Bartlett · Michael Jordan
[ PDF] 
Oral
Fri Jul 13 07:50 AM -- 08:00 AM (PDT) @ Victoria
Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace
In Deep Learning (Neural Network Architectures) 12
Yoonho Lee · Seungjin Choi
[ PDF] 
Oral
Fri Jul 13 07:50 AM -- 08:00 AM (PDT) @ K1
On the Limitations of First-Order Approximation in GAN Dynamics
In Deep Learning (Theory) 7
Jerry Li · Aleksander Madry · John Peebles · Ludwig Schmidt
[ PDF]  [ Video] 
Oral
Fri Jul 13 07:50 AM -- 08:00 AM (PDT) @ A7
Disentangled Sequential Autoencoder
In Generative Models 4
Yingzhen Li · Stephan Mandt
[ PDF]  [ Video] 
Oral
Fri Jul 13 07:50 AM -- 08:00 AM (PDT) @ A1
Self-Imitation Learning
In Reinforcement Learning 16
Junhyuk Oh · Yijie Guo · Satinder Singh · Honglak Lee
[ PDF] 
Oral
Fri Jul 13 07:50 AM -- 08:00 AM (PDT) @ A3
Communication-Computation Efficient Gradient Coding
In Parallel and Distributed Learning 3
Min Ye · Emmanuel Abbe
[ PDF] 
Oral
Fri Jul 13 07:50 AM -- 08:00 AM (PDT) @ K11
Rates of Convergence of Spectral Methods for Graphon Estimation
In Spectral Methods 1
Jiaming Xu
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:00 AM -- 08:20 AM (PDT) @ K1
On the Generalization of Equivariance and Convolution in Neural Networks to the Action of Compact Groups
In Deep Learning (Theory) 8
Risi Kondor · Shubhendu Trivedi
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:00 AM -- 08:20 AM (PDT) @ A4
Bayesian Coreset Construction via Greedy Iterative Geodesic Ascent
In Approximate Inference 3
Trevor Campbell · Tamara Broderick
[ PDF] 
Oral
Fri Jul 13 08:00 AM -- 08:20 AM (PDT) @ A9
Orthogonality-Promoting Distance Metric Learning: Convex Relaxation and Theoretical Analysis
In Optimization (Convex) 7
Pengtao Xie · Wei Wu · Yichen Zhu · Eric Xing
[ PDF] 
Oral
Fri Jul 13 08:00 AM -- 08:20 AM (PDT) @ A6
A Probabilistic Theory of Supervised Similarity Learning for Pointwise ROC Curve Optimization
In Statistical Learning Theory 5
Robin Vogel · Aurélien Bellet · Stéphan Clémençon
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:00 AM -- 08:20 AM (PDT) @ A5
Orthogonal Machine Learning: Power and Limitations
In Causal Inference 2
Ilias Zadik · Lester Mackey · Vasilis Syrgkanis
[ PDF]  [ PDF] 
Oral
Fri Jul 13 08:00 AM -- 08:20 AM (PDT) @ Victoria
WSNet: Compact and Efficient Networks Through Weight Sampling
In Deep Learning (Neural Network Architectures) 13
Xiaojie Jin · Yingzhen Yang · Ning Xu · Jianchao Yang · Nebojsa Jojic · Jiashi Feng · Shuicheng Yan
[ PDF] 
Oral
Fri Jul 13 08:00 AM -- 08:20 AM (PDT) @ A3
Analyzing Uncertainty in Neural Machine Translation
In Natural Language and Speech Processing 2
Myle Ott · Michael Auli · David Grangier · Marc'Aurelio Ranzato
[ PDF] 
Oral
Fri Jul 13 08:00 AM -- 08:20 AM (PDT) @ A7
Modeling Sparse Deviations for Compressed Sensing using Generative Models
In Generative Models 5
Manik Dhar · Aditya Grover · Stefano Ermon
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:00 AM -- 08:20 AM (PDT) @ A1
Mean Field Multi-Agent Reinforcement Learning
In Reinforcement Learning 17
Yaodong Yang · Rui Luo · Minne Li · Ming Zhou · Weinan Zhang · Jun Wang
[ PDF] 
Oral
Fri Jul 13 08:00 AM -- 08:20 AM (PDT) @ K11
Convolutional Imputation of Matrix Networks
In Matrix Factorization 2
Qingyun Sun · Mengyuan Yan · David Donoho · stephen boyd
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:20 AM -- 08:30 AM (PDT) @ A3
Generalization without Systematicity: On the Compositional Skills of Sequence-to-Sequence Recurrent Networks
In Natural Language and Speech Processing 2
Brenden Lake · Marco Baroni
[ PDF] 
Oral
Fri Jul 13 08:20 AM -- 08:30 AM (PDT) @ A4
CRVI: Convex Relaxation for Variational Inference
In Approximate Inference 3
Ghazal Fazelnia · John Paisley
[ PDF] 
Oral
Fri Jul 13 08:20 AM -- 08:40 AM (PDT) @ A1
Reinforcement Learning with Function-Valued Action Spaces for Partial Differential Equation Control
In Reinforcement Learning 17
Yangchen Pan · Amir-massoud Farahmand · Martha White · Saleh Nabi · Piyush Grover · Daniel Nikovski
[ PDF] 
Oral
Fri Jul 13 08:20 AM -- 08:40 AM (PDT) @ A5
Minimal I-MAP MCMC for Scalable Structure Discovery in Causal DAG Models
In Causal Inference 2
Raj Agrawal · Caroline Uhler · Tamara Broderick
[ PDF] 
Oral
Fri Jul 13 08:20 AM -- 08:30 AM (PDT) @ A6
Classification from Pairwise Similarity and Unlabeled Data
In Statistical Learning Theory 5
Han Bao · Gang Niu · Masashi Sugiyama
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:20 AM -- 08:30 AM (PDT) @ K11
Fast and Sample Efficient Inductive Matrix Completion via Multi-Phase Procrustes Flow
In Matrix Factorization 2
Xiao Zhang · Simon Du · Quanquan Gu
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:20 AM -- 08:30 AM (PDT) @ A7
oi-VAE: Output Interpretable VAEs for Nonlinear Group Factor Analysis
In Generative Models 5
Samuel Ainsworth · Nicholas J Foti · Adrian KC Lee · Emily Fox
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:20 AM -- 08:30 AM (PDT) @ A9
Celer: a Fast Solver for the Lasso with Dual Extrapolation
In Optimization (Convex) 7
Mathurin MASSIAS · Joseph Salmon · Alexandre Gramfort
[ PDF] 
Oral
Fri Jul 13 08:20 AM -- 08:30 AM (PDT) @ K1
Bounding and Counting Linear Regions of Deep Neural Networks
In Deep Learning (Theory) 8
Thiago Serra · Christian Tjandraatmadja · Srikumar Ramalingam
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:20 AM -- 08:40 AM (PDT) @ Victoria
StrassenNets: Deep Learning with a Multiplication Budget
In Deep Learning (Neural Network Architectures) 13
Michael Tschannen · Aran Khanna · Animashree Anandkumar
[ PDF] 
Oral
Fri Jul 13 08:30 AM -- 08:40 AM (PDT) @ A3
Adaptive Sampled Softmax with Kernel Based Sampling
In Natural Language and Speech Processing 2
Guy Blanc · Steffen Rendle
[ PDF] 
Oral
Fri Jul 13 08:30 AM -- 08:40 AM (PDT) @ A7
Noisin: Unbiased Regularization for Recurrent Neural Networks
In Generative Models 5
Adji Bousso Dieng · Rajesh Ranganath · Jaan Altosaar · David Blei
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:30 AM -- 08:40 AM (PDT) @ K11
On the Implicit Bias of Dropout
In Matrix Factorization 2
Poorya Mianjy · Raman Arora · Rene Vidal
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:30 AM -- 08:40 AM (PDT) @ A4
Stein Points
In Approximate Inference 3
Wilson Ye Chen · Lester Mackey · Jackson Gorham · Francois-Xavier Briol · Chris J Oates
[ PDF] 
Oral
Fri Jul 13 08:30 AM -- 08:40 AM (PDT) @ A9
Cut-Pursuit Algorithm for Regularizing Nonsmooth Functionals with Graph Total Variation
In Optimization (Convex) 7
Hugo Raguet · loic landrieu
[ PDF] 
Oral
Fri Jul 13 08:30 AM -- 08:40 AM (PDT) @ K1
DCFNet: Deep Neural Network with Decomposed Convolutional Filters
In Deep Learning (Theory) 8
Qiang Qiu · Xiuyuan Cheng · robert Calderbank · Guillermo Sapiro
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:30 AM -- 08:40 AM (PDT) @ A6
Comparison-Based Random Forests
In Statistical Learning Theory 5
Siavash Haghiri · Damien Garreau · Ulrike von Luxburg
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:40 AM -- 08:50 AM (PDT) @ A1
Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents
In Reinforcement Learning 17
Kaiqing Zhang · Zhuoran Yang · Han Liu · Tong Zhang · Tamer Basar
[ PDF] 
Oral
Fri Jul 13 08:40 AM -- 08:50 AM (PDT) @ A5
Accurate Inference for Adaptive Linear Models
In Causal Inference 2
Yash Deshpande · Lester Mackey · Vasilis Syrgkanis · Matt Taddy
[ PDF] 
Oral
Fri Jul 13 08:40 AM -- 08:50 AM (PDT) @ K11
A Unified Framework for Structured Low-rank Matrix Learning
In Matrix Factorization 2
Pratik Kumar Jawanpuria · Bamdev Mishra
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:40 AM -- 08:50 AM (PDT) @ A9
Efficient First-Order Algorithms for Adaptive Signal Denoising
In Optimization (Convex) 7
Dmitrii Ostrovskii · Zaid Harchaoui
[ PDF] 
Oral
Fri Jul 13 08:40 AM -- 08:50 AM (PDT) @ Victoria
Deep k-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions
In Deep Learning (Neural Network Architectures) 13
Junru Wu · Yue Wang · Zhenyu Wu · Zhangyang Wang · Ashok Veeraraghavan · Yingyan Lin
[ PDF] 
Oral
Fri Jul 13 08:40 AM -- 08:50 AM (PDT) @ K1
A Theoretical Explanation for Perplexing Behaviors of Backpropagation-based Visualizations
In Deep Learning (Theory) 8
Weili Nie · Yang Zhang · Ankit Patel
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:40 AM -- 08:50 AM (PDT) @ A3
Hierarchical Text Generation and Planning for Strategic Dialogue
In Natural Language and Speech Processing 2
Denis Yarats · Mike Lewis
[ PDF] 
Oral
Fri Jul 13 08:40 AM -- 08:50 AM (PDT) @ A7
Hierarchical Deep Generative Models for Multi-Rate Multivariate Time Series
In Generative Models 5
Zhengping Che · Sanjay Purushotham · Max Guangyu Li · Bo Jiang · Yan Liu
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:40 AM -- 08:50 AM (PDT) @ A4
Message Passing Stein Variational Gradient Descent
In Approximate Inference 3
Jingwei Zhuo · Chang Liu · Jiaxin Shi · Jun Zhu · Ning Chen · Bo Zhang
[ PDF] 
Oral
Fri Jul 13 08:40 AM -- 08:50 AM (PDT) @ A6
Analyzing the Robustness of Nearest Neighbors to Adversarial Examples
In Statistical Learning Theory 5
Yizhen Wang · Somesh Jha · Kamalika Chaudhuri
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:50 AM -- 09:00 AM (PDT) @ A7
Inter and Intra Topic Structure Learning with Word Embeddings
In Generative Models 5
He Zhao · Lan Du · Wray Buntine · Mingyuan Zhou
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:50 AM -- 09:00 AM (PDT) @ A6
Active Learning with Logged Data
In Statistical Learning Theory 5
Songbai Yan · Kamalika Chaudhuri · Tara Javidi
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:50 AM -- 09:00 AM (PDT) @ A9
An Algorithmic Framework of Variable Metric Over-Relaxed Hybrid Proximal Extra-Gradient Method
In Optimization (Convex) 7
Li Shen · Peng Sun · Yitong Wang · Wei Liu · Tong Zhang
[ PDF] 
Oral
Fri Jul 13 08:50 AM -- 09:00 AM (PDT) @ A1
The Uncertainty Bellman Equation and Exploration
In Reinforcement Learning 17
Brendan O'Donoghue · Ian Osband · Remi Munos · Vlad Mnih
[ PDF] 
Oral
Fri Jul 13 08:50 AM -- 09:00 AM (PDT) @ Victoria
Born Again Neural Networks
In Deep Learning (Neural Network Architectures) 13
Tommaso Furlanello · Zachary Lipton · Michael Tschannen · Laurent Itti · Anima Anandkumar
[ PDF] 
Oral
Fri Jul 13 08:50 AM -- 09:00 AM (PDT) @ A4
Pathwise Derivatives Beyond the Reparameterization Trick
In Approximate Inference 3
Martin Jankowiak · Fritz Obermeyer
[ PDF] 
Oral
Fri Jul 13 08:50 AM -- 09:00 AM (PDT) @ K11
Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers
In Matrix Factorization 2
Yao Ma · Alex Olshevsky · Csaba Szepesvari · Venkatesh Saligrama
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:50 AM -- 09:00 AM (PDT) @ A5
Detecting non-causal artifacts in multivariate linear regression models
In Causal Inference 2
Dominik Janzing · Bernhard Schölkopf
[ PDF]