|
Workshop
|
|
Meta-Learning General-Purpose Learning Algorithms with Transformers
Louis Kirsch · Luke Metz · James Harrison · Jascha Sohl-Dickstein
|
|
|
Poster
|
Thu 14:00
|
Amortized Proximal Optimization
Juhan Bae · Paul Vicol · Jeff Z. HaoChen · Roger Grosse
|
|
|
Poster
|
Wed 14:00
|
Near Instance-Optimal PAC Reinforcement Learning for Deterministic MDPs
Andrea Tirinzoni · Aymen Al Marjani · Emilie Kaufmann
|
|
|
Workshop
|
|
Graph Q-Learning for Combinatorial Optimization
Victoria Magdalena Dax · Jiachen Li · Kevin Leahy · Mykel J Kochenderfer
|
|
|
Workshop
|
|
Near-Optimal Deployment Efficiency in Reward-Free Reinforcement Learning with Linear Function Approximation
Dan Qiao · Yu-Xiang Wang
|
|
|
Panel
|
Tue 9:15
|
Panel 1A-1: Near-Optimal Collaborative Learning… & Minimax Regret for…
Clémence Réda · Daniel Vial
|
|
|
Poster
|
Wed 9:00
|
A Closer Look at Learned Optimization: Stability, Robustness, and Inductive Biases
James Harrison · Luke Metz · Jascha Sohl-Dickstein
|
|
|
Workshop
|
|
Understanding Curriculum Learning in Policy Optimization for Online Combinatorial Optimization
Runlong Zhou · Yuandong Tian · YI WU · Simon Du
|
|
|
Poster
|
Tue 14:00
|
EF-BV: A Unified Theory of Error Feedback and Variance Reduction Mechanisms for Biased and Unbiased Compression in Distributed Optimization
Laurent Condat · Kai Yi · Peter Richtarik
|
|
|
Workshop
|
|
Counterfactual Explanations Using Optimization With Constraint Learning
Donato Maragno · Tabea E. Röber · Ilker Birbil
|
|
|
Panel
|
Tue 9:15
|
Panel 1C-2: Reconstructing Training Data… & On Optimal Learning…
Gal Vardi · Idan Mehalel
|
|
|
Poster
|
Tue 14:00
|
Diversified Recommendations for Agents with Adaptive Preferences
William Brown · Arpit Agarwal
|
|
