Website: COLT 2020 (opens in new tab)
Microsoft is proud to be a Platinum sponsor of the Thirty-Third Annual Conference on Learning Theory (COLT) (opens in new tab), as well as Diamond partners for the Women in Machine Learning workshop (opens in new tab). Please see detailed information on our contributions to the program below.
Committee members
Publications Chair: Suriya Gunasekar
Senior Program Committee members: Adam Tauman Kalai, Alekh Agarwal, Alex Slivkins, Navin Goyal, Praneeth Netrapalli, Prateek Jain, Robert Schapire, Sébastien Bubeck, Vasilis Syrgkanis
Accepted papers
Thursday, July 9
5:30 AM – 8:00 AM PDT | Session 1A
Locally Private Hypothesis Selection
Sivakanth Gopi, Gautam Kamath, Janardhan D Kulkarni, Aleksandar Nikolov, Steven Wu, Huanyu Zhang
10:00 AM – 12:30 PM PDT | Session 1B
From Tree Matching to Sparse Graph Alignment
Luca Ganassali, Laurent Massoulie
10:00 AM – 12:30 PM PDT | Session 1B
Optimality and Approximation with Policy Gradient Methods in Markov Decision Processes
Alekh Agarwal, Sham Kakade, Jason Lee, Gaurav Mahajan
Friday, July 10
10:00 AM – 12:30 PM PDT | Session 2B
How to Trap a Gradient Flow
Dan Mikulincer, Sébastien Bubeck
5:00 PM – 7:00 PM PDT | Session 2C
Model-Based Reinforcement Learning with a Generative Model is Minimax Optimal
Alekh Agarwal, Sham Kakade, Lin Yang
Saturday, July 11
5:30 AM – 8:00 AM PDT | Session 3A
Estimation and Inference with Trees and Forests in High Dimensions
Vasilis Syrgkanis, Emmanouil Zampetakis
10:00 AM – 12:30 PM PDT | Session 3B
Coordination Without Communication: Optimal Regret in Two Players Multi-armed Bandits
Sébastien Bubeck, Thomas Budzinski
10:00 AM – 12:30 PM PDT | Session 3B
Gradient Descent Follows the Regularization Path for General Losses
Ziwei Ji, Miroslav Dudik, Robert Schapire, Matus Telgarsky
10:00 AM – 12:30 PM PDT | Session 3B
Non-Stochastic Multi-Player Multi-Armed Bandits: Optimal Rate With Collision Information, Sublinear Without
Sébastien Bubeck, Yuanzhi Li, Yuval Peres, Mark Sellke
10:00 AM – 12:30 PM PDT | Session 3B
Taking a Hint: How to Leverage Loss Predictors in Contextual Bandits?
Chen-Yu Wei, Haipeng Luo, Alekh Agarwal