Gaurav Mahajan
Cited by
Cited by
Optimality and approximation with policy gradient methods in markov decision processes
A Agarwal, SM Kakade, JD Lee, G Mahajan
Conference on Learning Theory, 64-66, 2020
On the theory of policy gradient methods: Optimality, approximation, and distribution shift
A Agarwal, SM Kakade, JD Lee, G Mahajan
Journal of Machine Learning Research 22 (98), 1-76, 2021
Agnostic -learning with Function Approximation in Deterministic Systems: Near-Optimal Bounds on Approximation Error and Sample Complexity
SS Du, JD Lee, G Mahajan, R Wang
Advances in Neural Information Processing Systems 33, 2020
Bilinear classes: A structural framework for provable generalization in rl
SS Du, SM Kakade, JD Lee, S Lovett, G Mahajan, W Sun, R Wang
arXiv preprint arXiv:2103.10897, 2021
Noise-tolerant, reliable active classification with comparison queries
M Hopkins, D Kane, S Lovett, G Mahajan
Conference on Learning Theory, 1957-2006, 2020
Point location and active learning: Learning halfspaces almost optimally
M Hopkins, DM Kane, S Lovett, G Mahajan
2020 61st Annual Symposium on Foundations of Computer Science (FOCS), 1034-1044, 2020
The system can't perform the operation now. Try again later.
Articles 1–6