Fair and Diverse DPP-Based Data Summarization. - L. Elisa Celis; Vijay Keswani; Damian Straszak; Amit Deshpande 001; Tarun Kathuria; Nisheeth K. Vishnoi (ICML, 2018)

Balanced News Using Constrained Bandit-based Personalization. - Sayash Kapoor; Vijay Keswani; Nisheeth K. Vishnoi; L. Elisa Celis (IJCAI, 2018)

Classification with Fairness Constraints: A Meta-Algorithm with Provable Guarantees. - L. Elisa Celis; Lingxiao Huang; Vijay Keswani; Nisheeth K. Vishnoi (FAT, 2019)

A dashboard for controlling polarization in personalization. - L. Elisa Celis; Sayash Kapoor; Farnood Salehi; Vijay Keswani; Nisheeth K. Vishnoi (AI Commun., 2019)

Improved Adversarial Learning for Fair Classification. - L. Elisa Celis; Vijay Keswani (CoRR, 2019)

Fair Distributions from Biased Samples: A Maximum Entropy Optimization Framework. - L. Elisa Celis; Vijay Keswani; Ozan Yildiz; Nisheeth K. Vishnoi (CoRR, 2019)

Data preprocessing to mitigate bias: A maximum entropy based approach. - L. Elisa Celis; Vijay Keswani; Nisheeth K. Vishnoi (ICML, 2020)

Implicit Diversity in Image Summarization. - L. Elisa Celis; Vijay Keswani (Proc. ACM Hum. Comput. Interact., 2020)

Towards Unbiased and Accurate Deferral to Multiple Experts. - Vijay Keswani; Matthew Lease; Krishnaram Kenthapadi (AIES, 2021)

Fair Classification with Noisy Protected Attributes: A Framework with Provable Guarantees. - L. Elisa Celis; Lingxiao Huang; Vijay Keswani; Nisheeth K. Vishnoi (ICML, 2021)

Auditing for Diversity Using Representative Examples. - Vijay Keswani; L. Elisa Celis (KDD, 2021)

Dialect Diversity in Text Summarization on Twitter. - Vijay Keswani; L. Elisa Celis (WWW, 2021)

Diverse Representation via Computational Participatory Elections - Lessons from a Case Study. - Florian Evéquoz; Johan Rochel; Vijay Keswani; L. Elisa Celis (EAAMO, 2022)

A Convergent and Dimension-Independent Min-Max Optimization Algorithm. - Vijay Keswani; Oren Mangoubi; Sushant Sachdeva; Nisheeth K. Vishnoi (ICML, 2022)

Designing Closed Human-in-the-loop Deferral Pipelines. - Vijay Keswani; Matthew Lease; Krishnaram Kenthapadi (CoRR, 2022)

Addressing Strategic Manipulation Disparities in Fair Classification. - Vijay Keswani; L. Elisa Celis (EAAMO, 2023)

Social Media Platform Structures and Their Implications (Short Paper). - Vijay Keswani (HHAI Workshops, 2023)

Designing Closed-Loop Models for Task Allocation. - Vijay Keswani; L. Elisa Celis; Krishnaram Kenthapadi; Matthew Lease (HHAI, 2023)

On The Stability of Moral Preferences: A Problem with Computational Elicitation Methods. - Kyle Boerstler; Vijay Keswani; Lok Chan; Jana Schaich Borg; Vincent Conitzer; Hoda Heidari; Walter Sinnott-Armstrong (AIES (1), 2024)

Algorithmic Fairness From the Perspective of Legal Anti-discrimination Principles. - Vijay Keswani; L. Elisa Celis (AIES (1), 2024)

On the Pros and Cons of Active Learning for Moral Preference Elicitation. - Vijay Keswani; Vincent Conitzer; Hoda Heidari; Jana Schaich Borg; Walter Sinnott-Armstrong (AIES (1), 2024)

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

Can AI Model the Complexities of Human Moral Decision-making? A Qualitative Study of Kidney Allocation Decisions. - Vijay Keswani; Vincent Conitzer; Walter Sinnott-Armstrong; Breanna K. Nguyen; Hoda Heidari; Jana Schaich Borg (CHI, 2025)