A Pairwise Fair and Community-preserving Approach to k-Center Clustering. - Brian Brubach; Darshan Chakrabarti; John P. Dickerson; Samir Khuller; Aravind Srinivasan; Leonidas Tsepenekas (ICML, 2020)

Fairness, Semi-Supervised Learning, and More: A General Framework for Clustering with Stochastic Pairwise Constraints. - Brian Brubach; Darshan Chakrabarti; John P. Dickerson; Aravind Srinivasan; Leonidas Tsepenekas (AAAI, 2021)

A New Notion of Individually Fair Clustering: α-Equitable k-Center. - Darshan Chakrabarti; John P. Dickerson; Seyed A. Esmaeili; Aravind Srinivasan; Leonidas Tsepenekas (AISTATS, 2022)

Optimal Local Bayesian Differential Privacy over Markov Chains. - Darshan Chakrabarti; Jie Gao 001; Aditya Saraf; Grant Schoenebeck; Fang-Yi Yu (AAMAS, 2022)

Learning Stackelberg Equilibria and Applications to Economic Design Games. - Gianluca Brero; Alon Eden; Darshan Chakrabarti; Matthias Gerstgrasser; Vincent Li; David C. Parkes (CoRR, 2022)

Block-Coordinate Methods and Restarting for Solving Extensive-Form Games. - Darshan Chakrabarti; Jelena Diakonikolas; Christian Kroer (NeurIPS, 2023)

Efficient Learning in Polyhedral Games via Best-Response Oracles. - Darshan Chakrabarti; Gabriele Farina; Christian Kroer (AAAI, 2024)

Automated Design of Affine Maximizer Mechanisms in Dynamic Settings. - Michael J. Curry; Vinzenz Thoma; Darshan Chakrabarti; Stephen McAleer; Christian Kroer; Tuomas Sandholm; Niao He; Sven Seuken (AAAI, 2024)

Implications of Distance over Redistricting Maps: Central and Outlier Maps. - Seyed A. Esmaeili; Darshan Chakrabarti; Hayley Grape; Brian Brubach (AAAI, 2024)

Contested Logistics: A Game-Theoretic Approach. - Jakub Cerný; Chun Kai Ling; Darshan Chakrabarti; Jingwen Zhang; Gabriele Farina; Christian Kroer; Garud Iyengar (GameSec, 2024)

Extensive-Form Game Solving via Blackwell Approachability on Treeplexes. - Darshan Chakrabarti; Julien Grand-Clément; Christian Kroer (NeurIPS, 2024)