On the von Neumann and Frank--Wolfe Algorithms with Away Steps

DOI10.1137/15M1009937zbMath1382.90071arXiv1507.04073MaRDI QIDQ2789610

Daniel J. Rodríguez, Negar Soheili, Javier F. Peña

Publication date: 2 March 2016

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

Full work available at URL: https://arxiv.org/abs/1507.04073

zbMATH Keywords

linear convergencevon Neumanncoordinate descentFrank-Wolfeaway steps

Mathematics Subject Classification ID

Minimax problems in mathematical programming (90C47) Quadratic programming (90C20) Methods of reduced gradient type (90C52)

Related Items (8)

Frank--Wolfe Methods with an Unbounded Feasible Region and Applications to Structured Learning ⋮ Solving conic systems via projection and rescaling ⋮ An Extended Frank--Wolfe Method with “In-Face” Directions, and Its Application to Low-Rank Matrix Completion ⋮ The smoothed complexity of Frank-Wolfe methods via conditioning of random matrices and polytopes ⋮ Rescaling Algorithms for Linear Conic Feasibility ⋮ The Minimum Euclidean-Norm Point in a Convex Polytope: Wolfe's Combinatorial Algorithm is Exponential ⋮ Polytope Conditioning and Linear Convergence of the Frank–Wolfe Algorithm ⋮ First-order methods for the convex hull membership problem

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