Dereziński, Michał

9 publications

COLT 2025 Faster Low-Rank Approximation and Kernel Ridge Regression via the Block-Nyström Method Sachin Garg, Michał Dereziński

NeurIPS 2024 Distributed Least Squares in Small Space via Sketching and Bias Reduction Sachin Garg, Kevin Tan, Michał Dereziński

NeurIPS 2024 Stochastic Newton Proximal Extragradient Method Ruichen Jiang, Michał Dereziński, Aryan Mokhtari

COLT 2023 Algorithmic Gaussianization Through Sketching: Converting Data into Sub-Gaussian Random Designs Michał Dereziński

JMLR 2022 Unbiased Estimators for Random Design Regression Michał Dereziński, Manfred K. Warmuth, Daniel Hsu

UAI 2021 LocalNewton: Reducing Communication Rounds for Distributed Learning Vipul Gupta, Avishek Ghosh, Michał Dereziński, Rajiv Khanna, Kannan Ramchandran, Michael W. Mahoney

COLT 2019 Fast Determinantal Point Processes via Distortion-Free Intermediate Sampling Michał Dereziński

COLT 2019 Minimax Experimental Design: Bridging the Gap Between Statistical and Worst-Case Approaches to Least Squares Regression Michał Dereziński, Kenneth L. Clarkson, Michael W. Mahoney, Manfred K. Warmuth

JMLR 2018 Reverse Iterative Volume Sampling for Linear Regression Michał Dereziński, Manfred K. Warmuth