Easily Parallelizable and Distributable Class of Algorithms for Structured Sparsity, with Optimal Acceleration

DOI10.1080/10618600.2019.1592757OpenAlexW3102760497MaRDI QIDQ3391206

Seyoon Ko, Joong-Ho Won, Donghyeon Yu

Publication date: 28 March 2022

Published in: Journal of Computational and Graphical Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1702.06234

zbMATH Keywords

nonsmooth optimizationoperator splittingdistributed computingsparsityGPUmonotone operator theory

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (4)

New convergence analysis of a primal-dual algorithm with large stepsizes ⋮ Data-Driven Nonsmooth Optimization ⋮ High-performance statistical computing in the computing environments of the 2020s ⋮ Lipschitz Certificates for Layered Network Structures Driven by Averaged Activation Operators

Uses Software

• TensorFlow

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