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cs.LG2026
Perfect Parallelization in Mini-Batch SGD with Classical Momentum Acceleration
Sachin Garg, Michał Dereziński
Accelerating stochastic gradient methods with classical momentum schemes, such as Polyak's heavy ball, has proven highly successful in training large-scale machine learning models,…
cs.LG2025
Turbocharging Gaussian Process Inference with Approximate Sketch-and-Project
Pratik Rathore, Zachary Frangella, Sachin Garg +3
Gaussian processes (GPs) play an essential role in biostatistics, scientific machine learning, and Bayesian optimization for their ability to provide probabilistic predictions and…