Stochastic proximal splitting algorithm for composite minimization
From MaRDI portal
Publication:2047212
DOI10.1007/s11590-021-01702-7zbMath1475.90106arXiv1912.02039OpenAlexW3121307036MaRDI QIDQ2047212
Paul Irofti, Andrei T. Patrascu
Publication date: 19 August 2021
Published in: Optimization Letters (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1912.02039
proximal pointMoreau envelopelinear convergence ratesublinear convergence rateparametric sparse representationstochastic proximal gradient algorithm
Related Items (2)
Sub-linear convergence of a stochastic proximal iteration method in Hilbert space ⋮ Sublinear Convergence of a Tamed Stochastic Gradient Descent Method in Hilbert Space
Uses Software
Cites Work
- A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
- Gradient methods for minimizing composite functions
- Pegasos: primal estimated sub-gradient solver for SVM
- Random algorithms for convex minimization problems
- Introductory lectures on convex optimization. A basic course.
- Inexact proximal stochastic gradient method for convex composite optimization
- Strong conical hull intersection property, bounded linear regularity, Jameson's property \((G)\), and error bounds in convex optimization
- Convergence of stochastic proximal gradient algorithm
- Stochastic First-Order Methods with Random Constraint Projection
- Ergodic Convergence of a Stochastic Proximal Point Algorithm
- Sparse and Redundant Representations
- Robust Stochastic Approximation Approach to Stochastic Programming
- On the interchange of subdifferentiation and conditional expectation for convex functionals
- Variational Analysis
- Accelerating the convergence of the method of alternating projections
- Nonasymptotic convergence of stochastic proximal point algorithms for constrained convex optimization
- A Proximal Gradient Algorithm for Decentralized Composite Optimization
- Stochastic Model-Based Minimization of Weakly Convex Functions
- Snake: A Stochastic Proximal Gradient Algorithm for Regularized Problems Over Large Graphs
- Stochastic (Approximate) Proximal Point Methods: Convergence, Optimality, and Adaptivity
- Regularized Iterative Stochastic Approximation Methods for Stochastic Variational Inequality Problems
This page was built for publication: Stochastic proximal splitting algorithm for composite minimization
