Stochastic Approximations and Perturbations in Forward-Backward Splitting for Monotone Operators
From MaRDI portal
Publication:2821630
zbMath1377.90109arXiv1507.07095MaRDI QIDQ2821630
Patrick L. Combettes, Jean-Christophe Pesquet
Publication date: 22 September 2016
Full work available at URL: https://arxiv.org/abs/1507.07095
convex optimizationstochastic approximationmonotone operatorsprimal-dual algorithmforward-backward algorithmproximal gradient method
Numerical optimization and variational techniques (65K10) Stochastic programming (90C15) Programming in abstract spaces (90C48) Applications of functional analysis in optimization, convex analysis, mathematical programming, economics (46N10)
Related Items (21)
A fully stochastic primal-dual algorithm ⋮ Stochastic forward-backward splitting for monotone inclusions ⋮ Unnamed Item ⋮ A random block-coordinate Douglas-Rachford splitting method with low computational complexity for binary logistic regression ⋮ A stochastic variance reduction algorithm with Bregman distances for structured composite problems ⋮ Stochastic Fixed-Point Iterations for Nonexpansive Maps: Convergence and Error Bounds ⋮ Variance reduction for root-finding problems ⋮ On the computation of equilibria in monotone and potential stochastic hierarchical games ⋮ Two stochastic optimization algorithms for convex optimization with fixed point constraints ⋮ String-averaging incremental stochastic subgradient algorithms ⋮ Stochastic quasi-Fejér block-coordinate fixed point iterations with random sweeping. II: Mean-square and linear convergence ⋮ Nonasymptotic convergence of stochastic proximal point algorithms for constrained convex optimization ⋮ Convergence of stochastic proximal gradient algorithm ⋮ Dynamical behavior of a stochastic forward-backward algorithm using random monotone operators ⋮ On the linear convergence of the stochastic gradient method with constant step-size ⋮ BinaryRelax: A Relaxation Approach for Training Deep Neural Networks with Quantized Weights ⋮ Blended coarse gradient descent for full quantization of deep neural networks ⋮ Asymptotic behavior of a dynamical system on a metric space ⋮ Stochastic proximal-gradient algorithms for penalized mixed models ⋮ Convergence analysis of the stochastic reflected forward-backward splitting algorithm ⋮ SABRINA: a stochastic subspace majorization-minimization algorithm
This page was built for publication: Stochastic Approximations and Perturbations in Forward-Backward Splitting for Monotone Operators
