28 citations · 105 across the 29 of their papers we have counts for
4 papers · 1 filter
Toward Optimal Second-Order Path-Length Guarantee for Adversarial Multi-Armed Bandits
Mengxiao Zhang
We study second-order path-length regret in adversarial -armed bandits against oblivious loss sequences. Bubeck et al. [2019] designed an algorithm that achieves $\widetilde{\ma…
Near-Optimal Stochastic Linear Bandits with Delay
Ofir Schlisselberg, Mengxiao Zhang, Yishay Mansour
We study stochastic linear bandits with delayed feedback under several delay models and establish near-optimal regret guarantees. Our results identify when delayed linear bandits e…
Near-Optimal Last-Iterate Convergence for Zero-Sum Games with Bandit Feedback and Opponent Actions
Soumita Hait, Ping Li, Haipeng Luo +1
Last-iterate convergence of learning dynamics in games has attracted significant recent attention. In two-player zero-sum games with bandit feedback, where only the loss of the sel…
Interaction-Grounded Learning for Contextual Markov Decision Processes with Personalized Feedback
Mengxiao Zhang, Yuheng Zhang, Haipeng Luo +1
In this paper, we study Interaction-Grounded Learning (IGL) [Xie et al., 2021], a paradigm designed for realistic scenarios where the learner receives indirect feedback generated b…