Stochastic Multi-Armed Bandits with Unrestricted Delay Distributions. - Tal Lancewicki; Shahar Segal; Tomer Koren; Yishay Mansour (ICML, 2021)

Learning Adversarial Markov Decision Processes with Delayed Feedback. - Tal Lancewicki; Aviv Rosenberg 002; Yishay Mansour (AAAI, 2022)

Cooperative Online Learning in Stochastic and Adversarial MDPs. - Tal Lancewicki; Aviv Rosenberg 002; Yishay Mansour (ICML, 2022)

Near-Optimal Regret for Adversarial MDP with Delayed Bandit Feedback. - Tiancheng Jin; Tal Lancewicki; Haipeng Luo; Yishay Mansour; Aviv Rosenberg 002 (NeurIPS, 2022)

A Unified Analysis of Nonstochastic Delayed Feedback for Combinatorial Semi-Bandits, Linear Bandits, and MDPs. - Dirk van der Hoeven; Lukas Zierahn; Tal Lancewicki; Aviv Rosenberg 002; Nicolò Cesa-Bianchi (COLT, 2023)

Regret Minimization and Convergence to Equilibria in General-sum Markov Games. - Liad Erez; Tal Lancewicki; Uri Sherman; Tomer Koren; Yishay Mansour (ICML, 2023)

Delay-Adapted Policy Optimization and Improved Regret for Adversarial MDP with Delayed Bandit Feedback. - Tal Lancewicki; Aviv Rosenberg 002; Dmitry Sotnikov (ICML, 2023)

Towards Natural Language-Driven Assembly Using Foundation Models. - Omkar Joglekar; Tal Lancewicki; Shir Kozlovsky; Vladimir Tchuiev; Zohar Feldman; Dotan Di Castro (CoRR, 2024)

Individual Regret in Cooperative Stochastic Multi-Armed Bandits. - Idan Barnea; Tal Lancewicki; Yishay Mansour (CoRR, 2024)

Delay as Payoff in MAB. - Ofir Schlisselberg; Ido Cohen 002; Tal Lancewicki; Yishay Mansour (AAAI, 2025)

Near-optimal Regret Using Policy Optimization in Online MDPs with Aggregate Bandit Feedback. - Tal Lancewicki; Yishay Mansour (CoRR, 2025)

Improved Best-of-Both-Worlds Regret for Bandits with Delayed Feedback. - Ofir Schlisselberg; Tal Lancewicki; Peter Auer; Yishay Mansour (CoRR, 2025)