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Oral
Thu Jun 13 11:00 AM -- 11:20 AM (PDT) @ Hall A
Understanding and correcting pathologies in the training of learned optimizers
In Deep Learning
Luke Metz · Niru Maheswaranathan · Jeremy Nixon · Daniel Freeman · Jascha Sohl-Dickstein
Oral
Thu Jun 13 11:20 AM -- 11:25 AM (PDT) @ Hall A
Demystifying Dropout
In Deep Learning
Hongchang Gao · Jian Pei · Heng Huang
[ Slides] 
Oral
Thu Jun 13 11:25 AM -- 11:30 AM (PDT) @ Hall A
Ladder Capsule Network
In Deep Learning
Taewon Jeong · Youngmin Lee · Heeyoung Kim
[ Slides] 
Oral
Thu Jun 13 11:30 AM -- 11:35 AM (PDT) @ Hall A
Unreproducible Research is Reproducible
In Deep Learning
Xavier Bouthillier · César Laurent · Pascal Vincent
[ Slides] 
Oral
Thu Jun 13 11:35 AM -- 11:40 AM (PDT) @ Hall A
Geometric Scattering for Graph Data Analysis
In Deep Learning
Feng Gao · Guy Wolf · Matthew Hirn
[ Slides] 
Oral
Thu Jun 13 11:40 AM -- 12:00 PM (PDT) @ Hall A
Robust Inference via Generative Classifiers for Handling Noisy Labels
In Deep Learning
Kimin Lee · Sukmin Yun · Kibok Lee · Honglak Lee · Bo Li · Jinwoo Shin
[ Slides] 
Oral
Thu Jun 13 12:00 PM -- 12:05 PM (PDT) @ Hall A
LIT: Learned Intermediate Representation Training for Model Compression
In Deep Learning
Animesh Koratana · Daniel Kang · Peter Bailis · Matei Zaharia
[ Slides] 
Oral
Thu Jun 13 12:05 PM -- 12:10 PM (PDT) @ Hall A
Analyzing and Improving Representations with the Soft Nearest Neighbor Loss
In Deep Learning
Nicholas Frosst · Nicolas Papernot · Geoffrey Hinton
[ Slides] 
Oral
Thu Jun 13 12:10 PM -- 12:15 PM (PDT) @ Hall A
What is the Effect of Importance Weighting in Deep Learning?
In Deep Learning
Jonathon Byrd · Zachary Lipton
[ Slides] 
Oral
Thu Jun 13 12:15 PM -- 12:20 PM (PDT) @ Hall A
Similarity of Neural Network Representations Revisited
In Deep Learning
Simon Kornblith · Mohammad Norouzi · Honglak Lee · Geoffrey Hinton
[ Slides]