Darshan Chakrabarti

According to our database, Darshan Chakrabarti authored at least 10 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Extensive-Form Game Solving via Blackwell Approachability on Treeplexes.

Darshan Chakrabarti, Julien Grand-Clément, Christian Kroer

CoRR, 2024

Implications of Distance over Redistricting Maps: Central and Outlier Maps.

Seyed A. Esmaeili, Darshan Chakrabarti, Hayley Grape, Brian Brubach

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 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

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Efficient Learning in Polyhedral Games via Best-Response Oracles.

Darshan Chakrabarti, Gabriele Farina, Christian Kroer

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Block-Coordinate Methods and Restarting for Solving Extensive-Form Games.

Darshan Chakrabarti, Jelena Diakonikolas, Christian Kroer

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

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

Optimal Local Bayesian Differential Privacy over Markov Chains.

Darshan Chakrabarti, Jie Gao, Aditya Saraf, Grant Schoenebeck, Fang-Yi Yu

Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

A New Notion of Individually Fair Clustering: α-Equitable k-Center.

Darshan Chakrabarti, John P. Dickerson, Seyed A. Esmaeili, Aravind Srinivasan, Leonidas Tsepenekas

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

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

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

A Pairwise Fair and Community-preserving Approach to k-Center Clustering.

Brian Brubach, Darshan Chakrabarti, John P. Dickerson, Samir Khuller, Aravind Srinivasan, Leonidas Tsepenekas

Proceedings of the 37th International Conference on Machine Learning, 2020