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Poster
Thu 0:30 Breaking the Moments Condition Barrier: No-Regret Algorithm for Bandits with Super Heavy-Tailed Payoffs
Han Zhong · Jiayi Huang · Lin Yang · Liwei Wang
Poster
Thu 8:30 Learning in two-player zero-sum partially observable Markov games with perfect recall
Tadashi Kozuno · Pierre Ménard · Remi Munos · Michal Valko
Poster
Tue 8:30 From Optimality to Robustness: Adaptive Re-Sampling Strategies in Stochastic Bandits
Dorian Baudry · Patrick Saux · Odalric-Ambrym Maillard
Poster
Thu 8:30 Beyond Bandit Feedback in Online Multiclass Classification
Dirk van der Hoeven · Federico Fusco · Nicolò Cesa-Bianchi
Poster
Thu 8:30 Risk Minimization from Adaptively Collected Data: Guarantees for Supervised and Policy Learning
Aurelien Bibaut · Nathan Kallus · Maria Dimakopoulou · Antoine Chambaz · Mark van der Laan
Affinity Workshop
Regret Minimization in Heavy-Tailed Bandits
Shubhada Agrawal · Sandeep Juneja · Wouter Koolen
Poster
Thu 16:30 Observation-Free Attacks on Stochastic Bandits
Yinglun Xu · Bhuvesh Kumar · Jacob Abernethy
Poster
Fri 8:30 A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning
Christoph Dann · Mehryar Mohri · Tong Zhang · Julian Zimmert
Poster
Thu 0:30 Improved Variance-Aware Confidence Sets for Linear Bandits and Linear Mixture MDP
Zihan Zhang · Jiaqi Yang · Xiangyang Ji · Simon Du
Poster
Thu 16:30 A Biased Graph Neural Network Sampler with Near-Optimal Regret
Qingru Zhang · David Wipf · Quan Gan · Le Song
Affinity Workshop
Gaussian Process Bandits with Aggregated Feedback
Mengyan Zhang · Russell Tsuchida · Cheng Soon Ong
Poster
Thu 0:30 Deep Bandits Show-Off: Simple and Efficient Exploration with Deep Networks
Rong Zhu · Mattia Rigotti