Optimal subgradient methods: computational properties for large-scale linear inverse problems
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Publication:2315075
DOI10.1007/s11081-018-9378-5zbMath1418.90190OpenAlexW2791720296MaRDI QIDQ2315075
Publication date: 31 July 2019
Published in: Optimization and Engineering (Search for Journal in Brave)
Full work available at URL: https://phaidra.univie.ac.at/o:937301
high-dimensional datasubgradient methodslinear inverse problemsstructured convex optimizationoptimal complexityfirst-order informationsparse nonsmooth optimization
Related Items (7)
An optimal subgradient algorithm with subspace search for costly convex optimization problems ⋮ Smoothing unadjusted Langevin algorithms for nonsmooth composite potential functions ⋮ Stochastic incremental mirror descent algorithms with Nesterov smoothing ⋮ OSGA ⋮ Accelerated first-order methods for large-scale convex optimization: nearly optimal complexity under strong convexity ⋮ Impulse noise removal by an adaptive trust-region method ⋮ A Bregman Forward-Backward Linesearch Algorithm for Nonconvex Composite Optimization: Superlinear Convergence to Nonisolated Local Minima
Uses Software
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