Parallel and Distributed algorithms for ML problems

2020/10/19 by Darina Dvinskikh, Dvinskikh, Darina, Alexander Gasnikov +4
Computer Science · Engineering · #Complexity and Algorithms in Graphs #FOS: Mathematics #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques

paper · pdf · doi:10.48550/arxiv.2010.09585

openalex publication_date 2020/10/19 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

In this paper we make a survey of modern parallel and distributed approaches to solve sum-type convex minimization problems come from ML applications.

Citations

• High probability generalization bounds for uniformly stable algorithms\n with nearly optimal rate
• Error Compensated Distributed SGD Can Be Accelerated

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