Learning Fair Classifiers: A Regularization-Inspired Approach. - Yahav Bechavod; Katrina Ligett (CoRR, 2017)

Equal Opportunity in Online Classification with Partial Feedback. - Yahav Bechavod; Katrina Ligett; Aaron Roth 001; Bo Waggoner; Zhiwei Steven Wu (NeurIPS, 2019)

Metric-Free Individual Fairness in Online Learning. - Yahav Bechavod; Christopher Jung 001; Zhiwei Steven Wu (NeurIPS, 2020)

Causal Feature Discovery through Strategic Modification. - Yahav Bechavod; Katrina Ligett; Zhiwei Steven Wu; Juba Ziani (CoRR, 2020)

Gaming Helps! Learning from Strategic Interactions in Natural Dynamics. - Yahav Bechavod; Katrina Ligett; Zhiwei Steven Wu; Juba Ziani (AISTATS, 2021)

Information Discrepancy in Strategic Learning. - Yahav Bechavod; Chara Podimata; Zhiwei Steven Wu; Juba Ziani (ICML, 2022)

Interview with Juba Ziani. - Yahav Bechavod (SIGecom Exch., 2022)

Individually Fair Learning with One-Sided Feedback. - Yahav Bechavod; Aaron Roth 001 (ICML, 2023)

Monotone Individual Fairness. - Yahav Bechavod (ICML, 2024)