Darshan Chakrabarti

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 17

Top Topics

Dissimilarity Matrix

Differential Privacy

Top Venues

Publications

Michael J. Curry, Vinzenz Thoma, Darshan Chakrabarti, Stephen McAleer, Christian Kroer, Tuomas Sandholm, Niao He, Sven Seuken
Automated Design of Affine Maximizer Mechanisms in Dynamic Settings. AAAI (2024)
Michael J. Curry, Vinzenz Thoma, Darshan Chakrabarti, Stephen McAleer, Christian Kroer, Tuomas Sandholm, Niao He, Sven Seuken
Automated Design of Affine Maximizer Mechanisms in Dynamic Settings. CoRR (2024)
Darshan Chakrabarti, Gabriele Farina, Christian Kroer
Efficient Learning in Polyhedral Games via Best-Response Oracles. AAAI (2024)
Seyed A. Esmaeili, Darshan Chakrabarti, Hayley Grape, Brian Brubach
Implications of Distance over Redistricting Maps: Central and Outlier Maps. AAAI (2024)
Darshan Chakrabarti, Julien Grand-Clément, Christian Kroer
Extensive-Form Game Solving via Blackwell Approachability on Treeplexes. CoRR (2024)
Darshan Chakrabarti, Jelena Diakonikolas, Christian Kroer
Block-Coordinate Methods and Restarting for Solving Extensive-Form Games. NeurIPS (2023)
Darshan Chakrabarti, Jelena Diakonikolas, Christian Kroer
Block-Coordinate Methods and Restarting for Solving Extensive-Form Games. CoRR (2023)
Darshan Chakrabarti, Gabriele Farina, Christian Kroer
Efficient Learning in Polyhedral Games via Best Response Oracles. CoRR (2023)
Darshan Chakrabarti, Jie Gao, Aditya Saraf, Grant Schoenebeck, Fang-Yi Yu
Optimal Local Bayesian Differential Privacy over Markov Chains. AAMAS (2022)
Darshan Chakrabarti, John P. Dickerson, Seyed A. Esmaeili, Aravind Srinivasan, Leonidas Tsepenekas
A New Notion of Individually Fair Clustering: α-Equitable k-Center. AISTATS (2022)
Gianluca Brero, Alon Eden, Darshan Chakrabarti, Matthias Gerstgrasser, Vincent Li, David C. Parkes
Learning Stackelberg Equilibria and Applications to Economic Design Games. CoRR (2022)
Darshan Chakrabarti, Jie Gao, Aditya Saraf, Grant Schoenebeck, Fang-Yi Yu
Optimal Local Bayesian Differential Privacy over Markov Chains. CoRR (2022)
Darshan Chakrabarti, John P. Dickerson, Seyed A. Esmaeili, Aravind Srinivasan, Leonidas Tsepenekas
A New Notion of Individually Fair Clustering: α-Equitable k-Center. CoRR (2021)
Brian Brubach, Darshan Chakrabarti, John P. Dickerson, Aravind Srinivasan, Leonidas Tsepenekas
Fairness, Semi-Supervised Learning, and More: A General Framework for Clustering with Stochastic Pairwise Constraints. CoRR (2021)
Brian Brubach, Darshan Chakrabarti, John P. Dickerson, Aravind Srinivasan, Leonidas Tsepenekas
Fairness, Semi-Supervised Learning, and More: A General Framework for Clustering with Stochastic Pairwise Constraints. AAAI (2021)
Brian Brubach, Darshan Chakrabarti, John P. Dickerson, Samir Khuller, Aravind Srinivasan, Leonidas Tsepenekas
A Pairwise Fair and Community-preserving Approach to k-Center Clustering. ICML (2020)
Brian Brubach, Darshan Chakrabarti, John P. Dickerson, Samir Khuller, Aravind Srinivasan, Leonidas Tsepenekas
A Pairwise Fair and Community-preserving Approach to k-Center Clustering. CoRR (2020)