Koulik Khamaru

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 23

Top Topics

Maximum Likelihood Estimator

Stochastic Approximation

Theoretical Guarantees

Top Venues

J. Mach. Learn. Res.

Publications

Koulik Khamaru
Stochastic Optimization with Constraints: A Non-asymptotic Instance-Dependent Analysis. CoRR (2024)
Mufang Ying, Koulik Khamaru, Cun-Hui Zhang
Adaptive Linear Estimating Equations. NeurIPS (2023)
Licong Lin, Koulik Khamaru, Martin J. Wainwright
Semi-parametric inference based on adaptively collected data. CoRR (2023)
Licong Lin, Mufang Ying, Suvrojit Ghosh, Koulik Khamaru, Cun-Hui Zhang
Statistical Limits of Adaptive Linear Models: Low-Dimensional Estimation and Inference. CoRR (2023)
Licong Lin, Mufang Ying, Suvrojit Ghosh, Koulik Khamaru, Cun-Hui Zhang
Statistical Limits of Adaptive Linear Models: Low-Dimensional Estimation and Inference. NeurIPS (2023)
Mufang Ying, Koulik Khamaru, Cun-Hui Zhang
Adaptive Linear Estimating Equations. CoRR (2023)
Koulik Khamaru, Eric Xia, Martin J. Wainwright, Michael I. Jordan
Instance-Dependent Confidence and Early Stopping for Reinforcement Learning. CoRR (2022)
Wenlong Mou, Koulik Khamaru, Martin J. Wainwright, Peter L. Bartlett, Michael I. Jordan
Optimal variance-reduced stochastic approximation in Banach spaces. CoRR (2022)
Koulik Khamaru, Ashwin Pananjady, Feng Ruan, Martin J. Wainwright, Michael I. Jordan
Is Temporal Difference Learning Optimal? An Instance-Dependent Analysis. SIAM J. Math. Data Sci. 3 (4) (2021)
Koulik Khamaru, Yash Deshpande, Lester Mackey, Martin J. Wainwright
Near-optimal inference in adaptive linear regression. CoRR (2021)
Koulik Khamaru, Eric Xia, Martin J. Wainwright, Michael I. Jordan
Instance-optimality in optimal value estimation: Adaptivity via variance-reduced Q-learning. CoRR (2021)
Nhat Ho, Koulik Khamaru, Raaz Dwivedi, Martin J. Wainwright, Michael I. Jordan, Bin Yu
Instability, Computational Efficiency and Statistical Accuracy. CoRR (2020)
Dhruv Malik, Ashwin Pananjady, Kush Bhatia, Koulik Khamaru, Peter L. Bartlett, Martin J. Wainwright
Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems. J. Mach. Learn. Res. 21 (2020)
Raaz Dwivedi, Nhat Ho, Koulik Khamaru, Martin J. Wainwright, Michael I. Jordan, Bin Yu
Sharp Analysis of Expectation-Maximization for Weakly Identifiable Models. AISTATS (2020)
Koulik Khamaru, Ashwin Pananjady, Feng Ruan, Martin J. Wainwright, Michael I. Jordan
Is Temporal Difference Learning Optimal? An Instance-Dependent Analysis. CoRR (2020)
Koulik Khamaru, Martin J. Wainwright
Convergence Guarantees for a Class of Non-convex and Non-smooth Optimization Problems. J. Mach. Learn. Res. 20 (2019)
Koulik Khamaru, Rahul Mazumder
Computation of the maximum likelihood estimator in low-rank factor analysis. Math. Program. 176 (1-2) (2019)
Raaz Dwivedi, Nhat Ho, Koulik Khamaru, Martin J. Wainwright, Michael I. Jordan, Bin Yu
Challenges with EM in application to weakly identifiable mixture models. CoRR (2019)
Dhruv Malik, Ashwin Pananjady, Kush Bhatia, Koulik Khamaru, Peter L. Bartlett, Martin J. Wainwright
Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems. AISTATS (2019)
Dhruv Malik, Ashwin Pananjady, Kush Bhatia, Koulik Khamaru, Peter L. Bartlett, Martin J. Wainwright
Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems. CoRR (2018)
Raaz Dwivedi, Nhat Ho, Koulik Khamaru, Martin J. Wainwright, Michael I. Jordan
Theoretical guarantees for EM under misspecified Gaussian mixture models. NeurIPS (2018)
Koulik Khamaru, Martin J. Wainwright
Convergence guarantees for a class of non-convex and non-smooth optimization problems. ICML (2018)
Koulik Khamaru, Martin J. Wainwright
Convergence guarantees for a class of non-convex and non-smooth optimization problems. CoRR (2018)
Rahul Biswas, Koulik Khamaru, Kaushik Kumar Majumdar
A Peak Synchronization Measure for Multiple Signals. IEEE Trans. Signal Process. 62 (17) (2014)