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Inference for Newton Methods with Accelerated Sketch-and-Project via Random Scaling
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-project solver (GAS), thereby mitigating the computational bottleneck of classical second-order methods. The GAS solver improves upon vanilla, unaccelerated sketch-and-project solvers by achieving accelerated convergence through Nesterov momentum updates, and accommodates a flexible projection metric whose proper choice further reduces computational cost. Building on this design, we establish asymptotic normality of
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- arXiv · AI, language, vision and robotics · 2026-09-11T04:16:59.000Z
First collected: 2026-09-20T18:42:18.733Z. This is not the publication date.