Toward Controlling Discrimination in Online Ad Auctions. - L. Elisa Celis; Anay Mehrotra; Nisheeth K. Vishnoi (ICML, 2019)

Fair Online Advertising. - L. Elisa Celis; Anay Mehrotra; Nisheeth K. Vishnoi (CoRR, 2019)

Interventions for ranking in the presence of implicit bias. - L. Elisa Celis; Anay Mehrotra; Nisheeth K. Vishnoi (FAT*, 2020)

The Effect of the Rooney Rule on Implicit Bias in the Long Term. - L. Elisa Celis; Chris Hays; Anay Mehrotra; Nisheeth K. Vishnoi (FAccT, 2021)

Mitigating Bias in Set Selection with Noisy Protected Attributes. - Anay Mehrotra; L. Elisa Celis (FAccT, 2021)

Fair Classification with Adversarial Perturbations. - L. Elisa Celis; Anay Mehrotra; Nisheeth K. Vishnoi (NeurIPS, 2021)

Input Validation with Symbolic Execution. - Anay Mehrotra; Ayush Bansal; Awanish Pandey; Subhajit Roy 001 (CoRR, 2021)

Fairness for AUC via Feature Augmentation. - Hortense Fong; Vineet Kumar 006; Anay Mehrotra; Nisheeth K. Vishnoi (FAccT, 2022)

Selection in the Presence of Implicit Bias: The Advantage of Intersectional Constraints. - Anay Mehrotra; Bary S. R. Pradelski; Nisheeth K. Vishnoi (FAccT, 2022)

Fair Ranking with Noisy Protected Attributes. - Anay Mehrotra; Nisheeth K. Vishnoi (NeurIPS, 2022)

Revisiting Group Fairness Metrics: The Effect of Networks. - Anay Mehrotra; Jeff Sachs; L. Elisa Celis (Proc. ACM Hum. Comput. Interact., 2022)

Sampling Individually-Fair Rankings that are Always Group Fair. - Sruthi Gorantla; Anay Mehrotra; Amit Deshpande; Anand Louis (AIES, 2023)

Subset Selection Based On Multiple Rankings in the Presence of Bias: Effectiveness of Fairness Constraints for Multiwinner Voting Score Functions. - Niclas Boehmer; L. Elisa Celis; Lingxiao Huang; Anay Mehrotra; Nisheeth K. Vishnoi (ICML, 2023)

Bias in Evaluation Processes: An Optimization-Based Model. - L. Elisa Celis; Amit Kumar 001; Anay Mehrotra; Nisheeth K. Vishnoi (NeurIPS, 2023)

Maximizing Submodular Functions for Recommendation in the Presence of Biases. - Anay Mehrotra; Nisheeth K. Vishnoi (WWW, 2023)

Smaller Confidence Intervals From IPW Estimators via Data-Dependent Coarsening (Extended Abstract). - Alkis Kalavasis; Anay Mehrotra; Manolis Zampetakis (COLT, 2024)

Efficient Statistics With Unknown Truncation, Polynomial Time Algorithms, Beyond Gaussians. - Jane H. Lee; Anay Mehrotra; Manolis Zampetakis (FOCS, 2024)

Fair Classification with Partial Feedback: An Exploration-Based Data Collection Approach. - Vijay Keswani; Anay Mehrotra; L. Elisa Celis (ICML, 2024)

Tree of Attacks: Jailbreaking Black-Box LLMs Automatically. - Anay Mehrotra; Manolis Zampetakis; Paul Kassianik; Blaine Nelson; Hyrum S. Anderson; Yaron Singer; Amin Karbasi (NeurIPS, 2024)

Smaller Confidence Intervals From IPW Estimators via Data-Dependent Coarsening. - Alkis Kalavasis; Anay Mehrotra; Manolis Zampetakis (CoRR, 2024)

Characterizations of Language Generation With Breadth. - Alkis Kalavasis; Anay Mehrotra; Grigoris Velegkas (CoRR, 2024)

What Makes Treatment Effects Identifiable? Characterizations and Estimators Beyond Unconfoundedness (Extended Abstract). - Yang Cai; Alkis Kalavasis; Katerina Mamali; Anay Mehrotra; Manolis Zampetakis (COLT, 2025)

On the Limits of Language Generation: Trade-Offs between Hallucination and Mode-Collapse. - Alkis Kalavasis; Anay Mehrotra; Grigoris Velegkas (STOC, 2025)

DDPM Score Matching and Distribution Learning. - Sinho Chewi; Alkis Kalavasis; Anay Mehrotra; Omar Montasser (CoRR, 2025)

Can SGD Select Good Fishermen? Local Convergence under Self-Selection Biases and Beyond. - Alkis Kalavasis; Anay Mehrotra; Felix Zhou 002 (CoRR, 2025)

Learning with Positive and Imperfect Unlabeled Data. - Jane H. Lee; Anay Mehrotra; Manolis Zampetakis (CoRR, 2025)

What Makes Treatment Effects Identifiable? Characterizations and Estimators Beyond Unconfoundedness. - Yang Cai; Alkis Kalavasis; Katerina Mamali; Anay Mehrotra; Manolis Zampetakis (CoRR, 2025)

On Union-Closedness of Language Generation. - Steve Hanneke; Amin Karbasi; Anay Mehrotra; Grigoris Velegkas (CoRR, 2025)