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stat.ML2026
Inference for Newton Methods with Accelerated Sketch-and-Project via Random Scaling
Xinchen Du, Elizaveta Rebrova, Michał Dereziński +1
We study an online sketched Newton method that approximates the Newton direction at each step via a state-of-the-art sketching solver, called the generalized accelerated sketch-and…
math.NA2026
Debiasing Random Oblique Projections for Subsampled OLS and Fast CUR in High Dimensions
Chengmei Niu, Sachin Garg, Michał Dereziński +1
Random sampling is a fundamental tool in modern machine learning and numerical linear algebra for reducing the computational cost of large-scale matrix problems. Existing analyses,…