Michał Dereziński

13 papers · 2018–2026 · 5 venues · across top CS/AI venues

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

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🗺️ Taxonomy Completionist (24) 🏃 Academic Marathon · Sprint 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Silver 🏆 Keyword Champion (3)

🧬 Topic Evolution 🗃️ Keyword Collector (69) 🔥 Unstoppable · Bronze 💎 Century Club · Bronze

Venues

COLT (6) JMLR (3) NeurIPS (2) IJCAI (1) UAI (1)

Top co-authors

Michael W. Mahoney (3) Sachin Garg (3) Manfred K. Warmuth (3) Rajiv Khanna (2) Xiaoyu Dong (1) Aryan Mokhtari (1) Raphael A Meyer (1) Kevin Tan (1) Ruichen Jiang (1) Avishek Ghosh (1)

Research topics

Machine Learning (13) Mathematics & Optimization (12) Optimization & Theory · Machine Learning (12) Optimization (11) Core Methods (6) Mathematics (4) Deep Learning (2) Optimization & Theory · Deep Learning (2) Computer Science (1) Application Areas (1) Foundations (1)

Keywords

least square (4) second-order method (3) volume sampling (3) importance sampling (2) distributed learning (2) communication efficiency (2) hessian oracle (2) condition number (2) least squares regression (2) unbiased estimator (2) low-rank approximation (2) linear regression (2) determinantal point process (2) nystrom method (1) spectral analysis (1) distributed optimization (1) strongly convex (1) stochastic gradient descent (1) matrix approximation (1) local averaging (1)

Papers

Last-Iterate Convergence of Randomized Kaczmarz and SGD with Greedy Step Size COLT 2026 The matrix-vector complexity of Ax=b COLT 2026 Faster Low-Rank Approximation and Kernel Ridge Regression via the Block-Nyström Method COLT 2025 Second-order Information Promotes Mini-Batch Robustness in Variance-Reduced Gradients JMLR 2025 Distributed Least Squares in Small Space via Sketching and Bias Reduction NeurIPS 2024 Stochastic Newton Proximal Extragradient Method NeurIPS 2024 Algorithmic Gaussianization through Sketching: Converting Data into Sub-gaussian Random Designs COLT 2023 Unbiased estimators for random design regression JMLR 2022 Improved Guarantees and a Multiple-descent Curve for Column Subset Selection and the Nystrom Method (Extended Abstract) IJCAI 2021 LocalNewton: Reducing communication rounds for distributed learning UAI 2021 Fast determinantal point processes via distortion-free intermediate sampling COLT 2019 Minimax experimental design: Bridging the gap between statistical and worst-case approaches to least squares regression COLT 2019 Reverse Iterative Volume Sampling for Linear Regression JMLR 2018