Low-Rank Spectral Optimization via Gauge Duality
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Publication:2811991
DOI10.1137/15M1034283zbMath1342.90115arXiv1508.00315OpenAlexW2288584783MaRDI QIDQ2811991
Ives MacÊdo, Michael P. Friedlander
Publication date: 10 June 2016
Published in: SIAM Journal on Scientific Computing (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1508.00315
convex optimizationsemidefinite optimizationphase retrievalsparse optimizationgauge dualitylow-rank solutions
Related Items
Applications of gauge duality in robust principal component analysis and semidefinite programming, Convex Geometry of the Generalized Matrix-Fractional Function, Revisiting Spectral Bundle Methods: Primal-Dual (Sub)linear Convergence Rates, Duality of optimization problems with gauge functions, Foundations of Gauge and Perspective Duality, Low-Rank Matrix Iteration Using Polynomial-Filtered Subspace Extraction, An Optimal-Storage Approach to Semidefinite Programming Using Approximate Complementarity, Total Variation--Based Phase Retrieval for Poisson Noise Removal, A semismooth Newton-based augmented Lagrangian algorithm for density matrix least squares problems
Uses Software
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