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SketchySGD: Reliable Stochastic Optimization via Randomized Curvature
Estimates

v1v2v3v4v5 (latest)

SketchySGD: Reliable Stochastic Optimization via Randomized Curvature Estimates

SIAM Journal on Mathematics of Data Science (SIMODS), 2022

16 November 2022

Zachary Frangella

Madeleine Udell

ArXiv (abs)PDF HTML

Papers citing "SketchySGD: Reliable Stochastic Optimization via Randomized Curvature Estimates"

4 / 4 papers shown

NysAct: A Scalable Preconditioned Gradient Descent using Nystrom ApproximationBigData Congress [Services Society] (BSS), 2024

301

0

0

10 Jun 2025

Turbocharging Gaussian Process Inference with Approximate Sketch-and-Project

Turbocharging Gaussian Process Inference with Approximate Sketch-and-Project

Zachary Frangella

Shaghayegh Fazliani

Michał Dereziński

Madeleine Udell

361

2

0

19 May 2025

SAPPHIRE: Preconditioned Stochastic Variance Reduction for Faster Large-Scale Statistical Learning

Zachary Frangella

Madeleine Udell

215

2

0

28 Jan 2025

Newton Meets Marchenko-Pastur: Massively Parallel Second-Order
Optimization with Hessian Sketching and Debiasing

Newton Meets Marchenko-Pastur: Massively Parallel Second-Order Optimization with Hessian Sketching and DebiasingInternational Conference on Learning Representations (ICLR), 2024

187

2

0

02 Oct 2024