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Gaurav Mahajan
Gaurav Mahajan
Yale University
Verified email at eng.ucsd.edu - Homepage
Title
Cited by
Cited by
Year
Optimality and approximation with policy gradient methods in markov decision processes
A Agarwal, SM Kakade, JD Lee, G Mahajan
Conference on Learning Theory (COLT 2020), 2020
3422020
On the theory of policy gradient methods: Optimality, approximation, and distribution shift
A Agarwal, SM Kakade, JD Lee, G Mahajan
The Journal of Machine Learning Research 22 (1), 4431-4506, 2021
3242021
Bilinear classes: A structural framework for provable generalization in rl
SS Du, SM Kakade, JD Lee, S Lovett, G Mahajan, W Sun, R Wang
International Conference on Machine Learning (ICML 2021) 139, 2021
1912021
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 (NeurIPS 2020), 2020
55*2020
Noise-tolerant, reliable active classification with comparison queries
M Hopkins, D Kane, S Lovett, G Mahajan
Conference on Learning Theory (COLT 2020), 1957-2006, 2020
222020
Realizable learning is all you need
M Hopkins, DM Kane, S Lovett, G Mahajan
Conference on Learning Theory (COLT 2022), 3015-3069, 2022
182022
Learning what to remember
R Bhattacharjee, G Mahajan
International Conference on Algorithmic Learning Theory (ALT 2022) 167, 70-89, 2022
152022
Point location and active learning: Learning halfspaces almost optimally
M Hopkins, DM Kane, S Lovett, G Mahajan
61st Annual Symposium on Foundations of Computer Science (FOCS 2020), 1034-1044, 2020
152020
Computational-statistical gaps in reinforcement learning
D Kane, S Liu, S Lovett, G Mahajan
Conference on Learning Theory (COLT 2022), 2022
142022
Learning hidden markov models using conditional samples
G Mahajan, S Kakade, A Krishnamurthy, C Zhang
The Thirty Sixth Annual Conference on Learning Theory, 2014-2066, 2023
22023
Exponential Hardness of Reinforcement Learning with Linear Function Approximation
S Liu, G Mahajan, D Kane, S Lovett, G Weisz, C Szepesvári
The Thirty Sixth Annual Conference on Learning Theory, 1588-1617, 2023
2*2023
Do PAC-Learners Learn the Marginal Distribution?
M Hopkins, DM Kane, S Lovett, G Mahajan
arXiv preprint arXiv:2302.06285, 2023
22023
Convergence of online k-means
G So, G Mahajan, S Dasgupta
International Conference on Artificial Intelligence and Statistics (AISTATS …, 2022
22022
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