Accelerated Stochastic Algorithms for Nonconvex Finite-Sum and Multiblock Optimization

DOI10.1137/18M1192536zbMath1431.90120arXiv1805.05411OpenAlexW2988725654WikidataQ126867295 ScholiaQ126867295MaRDI QIDQ5242931

Guanghui Lan, Yu Yang

Publication date: 8 November 2019

Published in: SIAM Journal on Optimization (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1805.05411

zbMATH Keywords

nonconvex optimizationaccelerationstochastic algorithmsfinite-sum optimizationmultiblock optimization

Mathematics Subject Classification ID

Semidefinite programming (90C22) Large-scale problems in mathematical programming (90C06) Nonconvex programming, global optimization (90C26) Numerical methods based on nonlinear programming (49M37)

Related Items (2)

Parallel sequential Monte Carlo for stochastic gradient-free nonconvex optimization ⋮ Recent Theoretical Advances in Non-Convex Optimization

Uses Software

• ISLR
• NC-OPT

Cites Work

• Unnamed Item
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• Accelerated Methods for NonConvex Optimization
• An Introduction to Statistical Learning
• Complexity of a Quadratic Penalty Accelerated Inexact Proximal Point Method for Solving Linearly Constrained Nonconvex Composite Programs
• Stochastic First- and Zeroth-Order Methods for Nonconvex Stochastic Programming
• The direct extension of ADMM for multi-block convex minimization problems is not necessarily convergent
• Mini-batch stochastic approximation methods for nonconvex stochastic composite optimization
• A general theory of concave regularization for high-dimensional sparse estimation problems

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