| Derivative-free methods for policy optimization: Guarantees for linear quadratic systems D Malik, A Pananjady, K Bhatia, K Khamaru, P Bartlett, M Wainwright The 22nd international conference on artificial intelligence and statistics …, 2019 | 164 | 2019 |
| Convergence Guarantees for a Class of Non-convex and Non-smooth Optimization Problems. K Khamaru, MJ Wainwright J. Mach. Learn. Res. 20 (154), 1-52, 2019 | 64 | 2019 |
| Singularity, Misspecification, and the Convergence Rate of EM R Dwivedi*, N Ho*, K Khamaru*, MI Jordan, MJ Wainwright, B Yu arXiv preprint arXiv:1810.00828, 2018 | 52 | 2018 |
| Is temporal difference learning optimal? an instance-dependent analysis K Khamaru, A Pananjady, F Ruan, MJ Wainwright, MI Jordan SIAM Journal on Mathematics of Data Science 3 (4), 1013-1040, 2021 | 44 | 2021 |
| Sharp analysis of expectation-maximization for weakly identifiable models R Dwivedi, N Ho, K Khamaru, M Wainwright, M Jordan, B Yu International Conference on Artificial Intelligence and Statistics, 1866-1876, 2020 | 18 | 2020 |
| A peak synchronization measure for multiple signals R Biswas, K Khamaru, KK Majumdar IEEE Transactions on Signal Processing 62 (17), 4390-4398, 2014 | 18 | 2014 |
| Instance-optimality in optimal value estimation: Adaptivity via variance-reduced Q-learning K Khamaru, E Xia, MJ Wainwright, MI Jordan arXiv preprint arXiv:2106.14352, 2021 | 15 | 2021 |
| Computation of the maximum likelihood estimator in low-rank factor analysis K Khamaru, R Mazumder Mathematical Programming 176, 279-310, 2019 | 14 | 2019 |
| Theoretical guarantees for EM under misspecified Gaussian mixture models R Dwivedi*, N Ho*, K Khamaru*, MJ Wainwright, ... Advances in Neural Information Processing Systems, 9704-9712, 2018 | 10 | 2018 |
| Instability, computational efficiency and statistical accuracy N Ho, K Khamaru, R Dwivedi, MJ Wainwright, MI Jordan, B Yu arXiv preprint arXiv:2005.11411, 2020 | 8 | 2020 |
| Challenges with EM in application to weakly identifiable mixture models R Dwivedi*, N Ho*, K Khamaru*, MJ Wainwright, MI Jordan, B Yu arXiv preprint arXiv:1902.00194, 2019 | 8 | 2019 |
| Near-optimal inference in adaptive linear regression K Khamaru, Y Deshpande, L Mackey, MJ Wainwright arXiv preprint arXiv:2107.02266, 2021 | 7 | 2021 |
| Optimal variance-reduced stochastic approximation in Banach spaces W Mou, K Khamaru, MJ Wainwright, PL Bartlett, MI Jordan arXiv preprint arXiv:2201.08518, 2022 | 5 | 2022 |
| Instance-Dependent Confidence and Early Stopping for Reinforcement Learning K Khamaru, E Xia, MJ Wainwright, MI Jordan arXiv preprint arXiv:2201.08536, 2022 | 3 | 2022 |
| Theoretical guarantees for the EM algorithm when applied to mis-specified Gaussian mixture models R Dwivedi, N Ho, K Khamaru, MJ Wainwright, MI Jordan Proceedings of the 32nd international conference on neural information …, 2018 | 1 | 2018 |
| Semi-parametric inference based on adaptively collected data L Lin, K Khamaru, MJ Wainwright arXiv preprint arXiv:2303.02534, 2023 | | 2023 |
| Guarantees for a few structured statistical problems K Khamaru UC Berkeley, 2022 | | 2022 |
| THE ANNALS NHO RAAZ DWIVEDI, K KHAMARU The Annals of Statistics 48 (6), 2020 | | 2020 |
| Randomized Trans-dimensional Transformation based Metropolis Coupled MCMC (RTTMC3): an application to mixture detection K Khamaru Indian Statistical Institute, Kolkata, 0 | | |
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyVerified email at cs.berkeley.edu
