A proximal quasi-Newton method based on memoryless modified symmetric rank-one formula

DOI10.3934/jimo.2022123OpenAlexW4288784966MaRDI QIDQ2691372

Yasushi Narushima, Shummin Nakayama

Publication date: 29 March 2023

Published in: Journal of Industrial and Management Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.3934/jimo.2022123

zbMATH Keywords

nonsmooth optimizationconvergence propertymemoryless quasi-Newton methodproximal quasi-Newton methodsymmetric rank one formula

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Large-scale problems in mathematical programming (90C06) Nonlinear programming (90C30) Methods of quasi-Newton type (90C53)

Uses Software

• CG_DESCENT
• LIBSVM
• Sparco
• UNLocBoX
• iPiano
• TFOCS
• PNOPT
• GitHub

Cites Work

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• A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
• An inertial forward-backward algorithm for the minimization of the sum of two nonconvex functions
• Practical inexact proximal quasi-Newton method with global complexity analysis
• Spectral scaling BFGS method
• A proximal difference-of-convex algorithm with extrapolation
• Templates for convex cone problems with applications to sparse signal recovery
• Inexact proximal memoryless quasi-Newton methods based on the Broyden family for minimizing composite functions
• Memoryless quasi-Newton methods based on spectral-scaling Broyden family for unconstrained optimization
• Forward-backward quasi-Newton methods for nonsmooth optimization problems
• Optimization theory and methods. Nonlinear programming
• A sufficient descent three-term conjugate gradient method via symmetric rank-one update for large-scale optimization
• iPiano: Inertial Proximal Algorithm for Nonconvex Optimization
• Proximal Splitting Methods in Signal Processing
• Proximal Newton-Type Methods for Minimizing Composite Functions
• Algorithm 851
• Two-Point Step Size Gradient Methods
• Conjugate Gradient Methods with Inexact Searches
• Sparse Reconstruction by Separable Approximation
• Forward-Backward Envelope for the Sum of Two Nonconvex Functions: Further Properties and Nonmonotone Linesearch Algorithms
• First-Order Methods in Optimization
• A MEMORYLESS SYMMETRIC RANK-ONE METHOD WITH SUFFICIENT DESCENT PROPERTY FOR UNCONSTRAINED OPTIMIZATION
• A new approach to symmetric rank-one updating
• On Quasi-Newton Forward-Backward Splitting: Proximal Calculus and Convergence
• A New Conjugate Gradient Method with Guaranteed Descent and an Efficient Line Search
• A modified BFGS method and its global convergence in nonconvex minimization
• Benchmarking optimization software with performance profiles.

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