Zeevi, Assaf

14 publications

AISTATS 2025 Learning the Pareto Front Using Bootstrapped Observation Samples Wonyoung Kim, Garud Iyengar, Assaf Zeevi

ICML 2025 Linear Bandits with Partially Observable Features Wonyoung Kim, Sungwoo Park, Garud Iyengar, Assaf Zeevi, Min-Hwan Oh

AISTATS 2024 A Doubly Robust Approach to Sparse Reinforcement Learning Wonyoung Kim, Garud Iyengar, Assaf Zeevi

ICML 2023 Bayesian Design Principles for Frequentist Sequential Learning Yunbei Xu, Assaf Zeevi

ALT 2023 Complexity Analysis of a Countable-Armed Bandit Problem Anand Kalvit, Assaf Zeevi

ICML 2023 Improved Algorithms for Multi-Period Multi-Class Packing Problems with Bandit Feedback Wonyoung Kim, Garud Iyengar, Assaf Zeevi

ICML 2023 Last Switch Dependent Bandits with Monotone Payoff Functions Ayoub Foussoul, Vineet Goyal, Orestis Papadigenopoulos, Assaf Zeevi

COLT 2021 Learning to Stop with Surprisingly Few Samples Daniel Russo, Assaf Zeevi, Tianyi Zhang

ICML 2021 Sparsity-Agnostic Lasso Bandit Min-Hwan Oh, Garud Iyengar, Assaf Zeevi

COLT 2018 A General Approach to Multi-Armed Bandits Under Risk Criteria Asaf B. Cassel, Shie Mannor, Assaf Zeevi

COLT 2017 Thompson Sampling for the MNL-Bandit Shipra Agrawal, Vashist Avadhanula, Vineet Goyal, Assaf Zeevi

ICML 2015 Online Time Series Prediction with Missing Data Oren Anava, Elad Hazan, Assaf Zeevi

NeurIPS 2014 Stochastic Multi-Armed-Bandit Problem with Non-Stationary Rewards Omar Besbes, Yonatan Gur, Assaf Zeevi

COLT 2010 Nonparametric Bandits with Covariates Philippe Rigollet, Assaf Zeevi