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Oral Session
Tue 16:15 Bandits, Reinforcement Learning / Optimization
Oral Session
Wed 9:15 Bandits, Reinforcement Learning / Learning Theory / Sparse Methods
Poster
Wed 12:45 DebiNet: Debiasing Linear Models with Nonlinear Overparameterized Neural Networks
Shiyun Xu · Zhiqi Bu
Poster
Tue 18:30 On the High Accuracy Limitation of Adaptive Property Estimation
Yanjun Han
Poster
Tue 14:00 No-Regret Algorithms for Private Gaussian Process Bandit Optimization
Abhimanyu Dubey
Poster
Tue 18:30 Parametric Programming Approach for More Powerful and General Lasso Selective Inference
Vo Nguyen Le Duy · Ichiro Takeuchi
Poster
Wed 12:45 Completing the Picture: Randomized Smoothing Suffers from the Curse of Dimensionality for a Large Family of Distributions
Yihan Wu · Aleksandar Bojchevski · Aleksei Kuvshinov · Stephan G√ľnnemann
Poster
Tue 18:30 Corralling Stochastic Bandit Algorithms
Raman Arora · Teodor Vanislavov Marinov · Mehryar Mohri
Poster
Wed 6:00 Logistic Q-Learning
Joan Bas Serrano · Sebastian Curi · Andreas Krause · Gergely Neu
Poster
Thu 7:30 No-regret Algorithms for Multi-task Bayesian Optimization
Sayak Ray Chowdhury · Aditya Gopalan
Poster
Wed 6:00 Logical Team Q-learning: An approach towards factored policies in cooperative MARL
Lucas Cassano · Ali H. Sayed
Poster
Thu 7:30 Instance-Wise Minimax-Optimal Algorithms for Logistic Bandits
Marc Abeille · Louis Faury · Clement Calauzenes