On gradient-based learning in continuous games E Mazumdar, LJ Ratliff, SS Sastry SIAM Journal on Mathematics of Data Science 2 (1), 103-131, 2020 | 182* | 2020 |
On finding local nash equilibria (and only local nash equilibria) in zero-sum games EV Mazumdar, MI Jordan, SS Sastry arXiv preprint arXiv:1901.00838, 2019 | 145 | 2019 |
Feedback linearization for uncertain systems via reinforcement learning T Westenbroek, D Fridovich-Keil, E Mazumdar, S Arora, V Prabhu, ... 2020 IEEE International Conference on Robotics and Automation (ICRA), 1364-1371, 2020 | 63* | 2020 |
Mathematical framework for activity-based cancer biomarkers GA Kwong, JS Dudani, E Carrodeguas, EV Mazumdar, SM Zekavat, ... Proceedings of the National Academy of Sciences 112 (41), 12627-12632, 2015 | 53 | 2015 |
Who leads and who follows in strategic classification? T Zrnic, E Mazumdar, S Sastry, M Jordan Advances in Neural Information Processing Systems 34, 15257-15269, 2021 | 48 | 2021 |
Gradient-based inverse risk-sensitive reinforcement learning E Mazumdar, LJ Ratliff, T Fiez, SS Sastry 2017 IEEE 56th Annual Conference on Decision and Control (CDC), 5796-5801, 2017 | 46* | 2017 |
Policy-Gradient Algorithms Have No Guarantees of Convergence in Linear Quadratic Games E Mazumdar, LJ Ratliff, MI Jordan, SS Sastry arXiv preprint arXiv:1907.03712, 2019 | 44* | 2019 |
Convergence Guarantees for Gradient-Based Learning in Continuous Games. B Chasnov, LJ Ratliff, E Mazumdar, S Burden Uncertainty in artificial intelligence, 2019 | 42* | 2019 |
On approximate Thompson sampling with Langevin algorithms E Mazumdar, A Pacchiano, Y Ma, M Jordan, P Bartlett International Conference on Machine Learning, 6797-6807, 2020 | 41* | 2020 |
Fast distributionally robust learning with variance-reduced min-max optimization Y Yu, T Lin, EV Mazumdar, M Jordan International Conference on Artificial Intelligence and Statistics, 1219-1250, 2022 | 26 | 2022 |
Global convergence to local minmax equilibrium in classes of nonconvex zero-sum games T Fiez, L Ratliff, E Mazumdar, E Faulkner, A Narang Advances in Neural Information Processing Systems 34, 29049-29063, 2021 | 22 | 2021 |
Langevin monte carlo for contextual bandits P Xu, H Zheng, EV Mazumdar, K Azizzadenesheli, A Anandkumar International Conference on Machine Learning, 24830-24850, 2022 | 21 | 2022 |
Zeroth-order methods for convex-concave min-max problems: Applications to decision-dependent risk minimization C Maheshwari, CY Chiu, E Mazumdar, S Sastry, L Ratliff International Conference on Artificial Intelligence and Statistics, 6702-6734, 2022 | 17 | 2022 |
To observe or not to observe: Queuing game framework for urban parking LJ Ratliff, C Dowling, E Mazumdar, B Zhang 2016 IEEE 55th Conference on Decision and Control (CDC), 5286-5291, 2016 | 17 | 2016 |
Understanding the impact of parking on urban mobility via routing games on queue-flow networks D Calderone, E Mazumdar, LJ Ratliff, SS Sastry 2016 IEEE 55th Conference on Decision and Control (CDC), 7605-7610, 2016 | 14 | 2016 |
Local Nash Equilibria are Isolated, Strict Local Nash Equilibria in 'Almost All' Zero-Sum Continuous Games E Mazumdar, L Ratliff arXiv preprint arXiv:2002.01007, 2020 | 13 | 2020 |
Algorithmic collective action in machine learning M Hardt, E Mazumdar, C Mendler-Dünner, T Zrnic International Conference on Machine Learning, 12570-12586, 2023 | 10 | 2023 |
Adaptive control for linearizable systems using on-policy reinforcement learning T Westenbroek, E Mazumdar, D Fridovich-Keil, V Prabhu, CJ Tomlin, ... 2020 59th IEEE Conference on Decision and Control (CDC), 118-125, 2020 | 10 | 2020 |
On the analysis of cyclic drug schedules for cancer treatment using switched dynamical systems MP Chapman, EV Mazumdar, E Langer, R Sears, CJ Tomlin 2018 IEEE Conference on Decision and Control (CDC), 3503-3509, 2018 | 10 | 2018 |
A multi-armed bandit approach for online expert selection in markov decision processes E Mazumdar, R Dong, VR Royo, C Tomlin, SS Sastry arXiv preprint arXiv:1707.05714, 2017 | 10 | 2017 |