Conference schedule
The conference schedule will be modified a bit from previous years; see the changelog for more details.
The table below provides an overview of the conference schedule and the colocation with COLT.
| COLT | ICML (daytime) | ICML (evening) | ||
|---|---|---|---|---|
| 25 June | Monday | COLT Sessions | ||
| Tuesday | COLT Sessions | ICML Tutorials | ICML Reception | |
| Wednesday | ICML/COLT Joint day | Poster Session 1 | ||
| Thursday | ICML Sessions | Poster Session 2 | ||
| Friday | ICML Sessions | Poster Session 3 | ||
| Saturday | Workshops | Banquet | ||
| 1 July | Sunday | Workshops | ||
ICML program overview
All plenary sessions will be split between AT LT 2, AT LT 4, and AT LT 5. Volunteers will direct you to the appropriate lecture theatre.
Statistical Learning Theory in Reinforcement Learning and Approximate Dynamic Programming
AT LT5, 2h30Probabilistic Topic Models
AT LT1, 2h30Performance Evaluation for Learning Algorithms: Techniques, Application and Issues
12:30 AT LT4, 1hMirror Descent and Saddle Point First Order Algorithms (Invited COLT Tutorial)
AT LT5, 2h30Representation Learning
Prediction, Belief, and Markets
15:30 AT LT1, 2h30PAC-Bayesian Analysis in Supervised, Unsupervised, and Reinforcement Learning
AT LT4, 2h30Causal Inference - Conditional Independency and Beyond
AT LT5, 2h30Spectral Approaches to Learning Latent Variable Models
18:30 Scottish National Gallery, The MoundConference reception. Leave from IF just after 18:00
June 27
Wednesday
Welcome
8:40Invited talk plenary
Sethu Muthukrishnan
“Modern Algorithmic Tools for Analyzing Data Streams”
ICML Best paper award plenary
10:00Coffee
10:30Session 1A, 1B, 1C, 1D
12:10Lunch
14:00Invited talk plenary
Dimitris Achlioptas
“Algorithmic Phase Transitions in Constraint Satisfaction Problems”
COLT Best paper award plenary
15:30Coffee
16:00Session 2A, 2B, 2C, 2D
17:40Posters
18:00Open problem session plenary
June 28
Thursday
Session 3A, 3B, 3C, 3D, 3E
10:00Coffee
10:30Session 4A, 4B, 4C, 4D, 4E
12:10Lunch
14:00Invited talk plenary
David MacKay
“Information Theory and Sustainable Energy”
Test-of-time award talk plenary
Risi Kondor, John Lafferty
“Diffusion Kernels on Graphs and Other Discrete Input Spaces”
Coffee
16:00Session 5A, 5B, 5C, 5D, 5E
17:40Posters
Session 3
- 3A - Optimization algorithms 2 AT LT4
- 3B - Clustering 1 AT LT5
- 3C - Privacy, Anonymity, and Security AT LT1
- 3D - Ranking and Preference Learning AT LT2
- 3E - Nonparametric Bayesian inference AT LT3
Session 4
- 4A - Feature selection and dimensionality reduction 1 AT LT4
- 4B - Online learning 1 AT LT5
- 4C - Supervised learning 1 AT LT1
- 4D - Transfer and Multi-Task Learning AT LT2
- 4E - Graphical models AT LT3
Session 5
June 29
Friday
Session 6A, 6B, 6C, 6D, 6E
10:00Coffee
10:30Session 7A, 7B, 7C, 7D, 7E
12:10Lunch
14:00Session 8A, 8B, 8C, 8D, 8E
15:40Coffee
16:10Invited talk
Yann LeCun
“Learning Hierarchies of Invariant Features”
Applications talk plenary
Kiri Wagstaff
“Machine Learning that Matters”
Business meeting
17:40Posters
Session 6
- 6A - Semi-supervised learning AT LT4
- 6B - Reinforcement learning 3 AT LT5
- 6C - Applications AT LT1
- 6D - Time-Series Analysis AT LT2
- 6E - Graph-based learning AT LT3
Session 7
- 7A - Invited Applications AT LT
- 7B - Reinforcement learning 4 AT LT
- 7C - Clustering 2 AT LT
- 7D - Supervised learning 2 AT LT
- 7E - Probabilistic Models AT LT
Session 8
ICML Full program
Statistical linear estimation with penalized estimators: an application to reinforcement learning
Session 4A — Feature selection and dimensionality reduction 1
chair Kilian Weinberger, room AT LT 4
Information-Theoretical Learning of Discriminative Clusters for Unsupervised Domain Adaptation
Session 8C — Feature selection and dimensionality reduction
chair Andrea Danyluk, room AT LT 1