Optimal Algorithm for Bayesian Incentive-Compatible. - Lee Cohen 001; Yishay Mansour (CoRR, 2018)

Optimal Algorithm for Bayesian Incentive-Compatible Exploration. - Lee Cohen 001; Yishay Mansour (EC, 2019)

Efficient Candidate Screening Under Multiple Tests and Implications for Fairness. - Lee Cohen 001; Zachary C. Lipton; Yishay Mansour (FORC, 2020)

Sample Complexity of Uniform Convergence for Multicalibration. - Eliran Shabat; Lee Cohen 001; Yishay Mansour (NeurIPS, 2020)

Dueling Bandits with Team Comparisons. - Lee Cohen 001; Ulrike Schmidt-Kraepelin; Yishay Mansour (NeurIPS, 2021)

Modeling Attrition in Recommender Systems with Departing Bandits. - Omer Ben-Porat; Lee Cohen 001; Liu Leqi; Zachary C. Lipton; Yishay Mansour (AAAI, 2022)

Finding Safe Zones of policies Markov Decision Processes. - Lee Cohen 001; Yishay Mansour; Michal Moshkovitz (CoRR, 2022)

Topics in Machine Learning, Reinforcement Learning and Societal Challenges - Lee Cohen 001 (2022)

Sequential Strategic Screening. - Lee Cohen 001; Saeed Sharifi-Malvajerdi; Kevin Stangl; Ali Vakilian; Juba Ziani (ICML, 2023)

Finding Safe Zones of Markov Decision Processes Policies. - Lee Cohen 001; Yishay Mansour; Michal Moshkovitz (NeurIPS, 2023)

Eliciting User Preferences for Personalized Multi-Objective Decision Making through Comparative Feedback. - Han Shao; Lee Cohen 001; Avrim Blum; Yishay Mansour; Aadirupa Saha; Matthew R. Walter (NeurIPS, 2023)

Learnability Gaps of Strategic Classification. - Lee Cohen 001; Yishay Mansour; Shay Moran; Han Shao (COLT, 2024)

Incentivized Collaboration in Active Learning. - Lee Cohen 001; Han Shao (FORC, 2024)

Bayesian Strategic Classification. - Lee Cohen 001; Saeed Sharifi-Malvajerdi; Kevin Stangl; Ali Vakilian; Juba Ziani (NeurIPS, 2024)

Probably Approximately Precision and Recall Learning. - Lee Cohen 001; Yishay Mansour; Shay Moran; Han Shao (CoRR, 2024)