Gaurav Mahajan

29 papers A* 9A 1B 2Journal 15Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	B	`conf`	Do PAC-Learners Learn the Marginal Distribution? ALT Max Hopkins, Daniel M. Kane, Shachar Lovett, Gaurav Mahajan
2024	—	`conf`	Deciphering EEG Waves for the Generation of Images. BCI Gaurav Mahajan, Jeevan R, Divija L, P. Deekshitha Kumari, Surabhi Narayan
2024	J	`jnl`	Improved classical shadows from local symmetries in the Schur basis. CoRR Daniel Grier, Sihan Liu, Gaurav Mahajan
2024	J	`jnl`	Realizable Learning is All You Need. TheoretiCS Max Hopkins, Daniel M. Kane, Shachar Lovett, Gaurav Mahajan
2023	—	`—`	Computational and Statistical Complexity of Learning in Sequential Models Gaurav Mahajan
2023	J	`jnl`	Do PAC-Learners Learn the Marginal Distribution? CoRR Max Hopkins, Daniel M. Kane, Shachar Lovett, Gaurav Mahajan
2023	A*	`conf`	Exponential Hardness of Reinforcement Learning with Linear Function Approximation. COLT Sihan Liu, Gaurav Mahajan, Daniel Kane, Shachar Lovett, Gellért Weisz, Csaba Szepesvári
2023	J	`jnl`	Exponential Hardness of Reinforcement Learning with Linear Function Approximation. CoRR Daniel Kane, Sihan Liu, Shachar Lovett, Gaurav Mahajan, Csaba Szepesvári, Gellért Weisz
2023	A*	`conf`	Learning Hidden Markov Models Using Conditional Samples. COLT Gaurav Mahajan, Sham M. Kakade, Akshay Krishnamurthy, Cyril Zhang
2023	J	`jnl`	Learning Hidden Markov Models Using Conditional Samples. CoRR Sham M. Kakade, Akshay Krishnamurthy, Gaurav Mahajan, Cyril Zhang
2022	A*	`conf`	Computational-Statistical Gap in Reinforcement Learning. COLT Daniel Kane, Sihan Liu, Shachar Lovett, Gaurav Mahajan
2022	J	`jnl`	Computational-Statistical Gaps in Reinforcement Learning. CoRR Daniel Kane, Sihan Liu, Shachar Lovett, Gaurav Mahajan
2022	A	`conf`	Convergence of online k-means. AISTATS Geelon So, Gaurav Mahajan, Sanjoy Dasgupta
2022	J	`jnl`	Convergence of online k-means. CoRR Sanjoy Dasgupta, Gaurav Mahajan, Geelon So
2022	B	`conf`	Learning what to remember. ALT Robi Bhattacharjee, Gaurav Mahajan
2022	J	`jnl`	Learning what to remember. CoRR Robi Bhattacharjee, Gaurav Mahajan
2022	A*	`conf`	Realizable Learning is All You Need. COLT Max Hopkins, Daniel M. Kane, Shachar Lovett, Gaurav Mahajan
2021	A*	`conf`	Bilinear Classes: A Structural Framework for Provable Generalization in RL. ICML Simon S. Du, Sham M. Kakade, Jason D. Lee, Shachar Lovett, Gaurav Mahajan, Wen Sun, Ruosong Wang
2021	J	`jnl`	Bilinear Classes: A Structural Framework for Provable Generalization in RL. CoRR Simon S. Du, Sham M. Kakade, Jason D. Lee, Shachar Lovett, Gaurav Mahajan, Wen Sun, Ruosong Wang
2021	J	`jnl`	On the Theory of Policy Gradient Methods: Optimality, Approximation, and Distribution Shift. J. Mach. Learn. Res. Alekh Agarwal, Sham M. Kakade, Jason D. Lee, Gaurav Mahajan
2021	J	`jnl`	Realizable Learning is All You Need. CoRR Max Hopkins, Daniel M. Kane, Shachar Lovett, Gaurav Mahajan
2020	A*	`conf`	Agnostic $Q$-learning with Function Approximation in Deterministic Systems: Near-Optimal Bounds on Approximation Error and Sample Complexity. NeurIPS Simon S. Du, Jason D. Lee, Gaurav Mahajan, Ruosong Wang
2020	J	`jnl`	Agnostic Q-learning with Function Approximation in Deterministic Systems: Tight Bounds on Approximation Error and Sample Complexity. CoRR Simon S. Du, Jason D. Lee, Gaurav Mahajan, Ruosong Wang
2020	A*	`conf`	Noise-tolerant, Reliable Active Classification with Comparison Queries. COLT Max Hopkins, Daniel Kane, Shachar Lovett, Gaurav Mahajan
2020	J	`jnl`	Noise-tolerant, Reliable Active Classification with Comparison Queries. CoRR Max Hopkins, Daniel Kane, Shachar Lovett, Gaurav Mahajan
2020	A*	`conf`	Optimality and Approximation with Policy Gradient Methods in Markov Decision Processes. COLT Alekh Agarwal, Sham M. Kakade, Jason D. Lee, Gaurav Mahajan
2020	A*	`conf`	Point Location and Active Learning: Learning Halfspaces Almost Optimally. FOCS Max Hopkins, Daniel Kane, Shachar Lovett, Gaurav Mahajan
2020	J	`jnl`	Point Location and Active Learning: Learning Halfspaces Almost Optimally. CoRR Max Hopkins, Daniel M. Kane, Shachar Lovett, Gaurav Mahajan
2019	J	`jnl`	Optimality and Approximation with Policy Gradient Methods in Markov Decision Processes. CoRR Alekh Agarwal, Sham M. Kakade, Jason D. Lee, Gaurav Mahajan