Gaurav Mahajan

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Jason D. LeeAssociate Professor of Electrical Engineering and Computer Science, Princeton UniversityPotvrđena adresa e-pošte na princeton.edu
Sham M KakadeHarvard UniversityPotvrđena adresa e-pošte na seas.harvard.edu
Shachar LovettAssociate Professor of Computer Science, University of California San DiegoPotvrđena adresa e-pošte na eng.ucsd.edu
Alekh AgarwalGooglePotvrđena adresa e-pošte na google.com
Daniel KaneUniversity of California, San DiegoPotvrđena adresa e-pošte na ucsd.edu
Simon Shaolei DuAssistant Professor, School of Computer Science and Engineering, University of WashingtonPotvrđena adresa e-pošte na cs.washington.edu
Ruosong WangAssistant Professor, Peking UniversityPotvrđena adresa e-pošte na pku.edu.cn
Max HopkinsPrinceton UniversityPotvrđena adresa e-pošte na princeton.edu
Wen SunAssistant Professor, Cornell UniversityPotvrđena adresa e-pošte na cornell.edu
Sihan LiuUniversity of California San DiegoPotvrđena adresa e-pošte na ucsd.edu
Csaba SzepesvariDeepMind & University of AlbertaPotvrđena adresa e-pošte na cs.ualberta.ca
Cyril ZhangMicrosoft AIPotvrđena adresa e-pošte na microsoft.com
Gellért WeiszDeepMind, UCL, gellert@google.comPotvrđena adresa e-pošte na google.com
Akshay KrishnamurthyUniversity of Massachusetts AmherstPotvrđena adresa e-pošte na cs.umass.edu
Geelon SoUniversity of California, San DiegoPotvrđena adresa e-pošte na ucsd.edu
Sanjoy DasguptaProfessor of Computer Science, University of California - San DiegoPotvrđena adresa e-pošte na ucsd.edu
Daniel GrierAssistant Professor, University of California, San DiegoPotvrđena adresa e-pošte na ucsd.edu

Prati

Gaurav Mahajan

Postdoctoral Associate, Yale University

Potvrđena adresa e-pošte na yale.edu - Početna stranica

Theoretical Computer Science


Naslov Poredaj po navodima Poredaj po godini Poredaj po naslovu	Citirano Citirano	Godina
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	487	2021
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	405	2020
Bilinear classes: A structural framework for provable generalization in rl S Du, S Kakade, J Lee, S Lovett, G Mahajan, W Sun, R Wang International Conference on Machine Learning, 2826-2836, 2021	242	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, 22327-22337, 2020	63*	2020
Realizable learning is all you need M Hopkins, DM Kane, S Lovett, G Mahajan Conference on Learning Theory, 3015-3069, 2022	27	2022
Noise-tolerant, reliable active classification with comparison queries M Hopkins, D Kane, S Lovett, G Mahajan Conference on Learning Theory, 1957-2006, 2020	27	2020
Computational-statistical gap in reinforcement learning D Kane, S Liu, S Lovett, G Mahajan Conference on Learning Theory, 1282-1302, 2022	25	2022
Point location and active learning: Learning halfspaces almost optimally M Hopkins, D Kane, S Lovett, G Mahajan 2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS …, 2020	20	2020
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	6*	2023
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	5	2023
Do PAC-Learners Learn the Marginal Distribution? M Hopkins, DM Kane, S Lovett, G Mahajan arXiv preprint arXiv:2302.06285, 2023	4	2023
Convergence of online k-means G So, G Mahajan, S Dasgupta International Conference on Artificial Intelligence and Statistics, 8534-8569, 2022	4	2022
Learning what to remember R Bhattacharjee, G Mahajan International Conference on Algorithmic Learning Theory, 70-89, 2022	2	2022
Improved classical shadows from local symmetries in the Schur basis D Grier, S Liu, G Mahajan arXiv preprint arXiv:2405.09525, 2024	1	2024
Learning hidden markov models using conditional samples SM Kakade, A Krishnamurthy, G Mahajan, C Zhang arXiv preprint arXiv:2302.14753, 2023	1	2023
Computational and Statistical Complexity of Learning in Sequential Models G Mahajan University of California, San Diego, 2023		2023
Convergence of online -means S Dasgupta, G Mahajan, G So arXiv preprint arXiv:2202.10640, 2022		2022

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