On stochastic gradient and subgradient methods with adaptive steplength sequences
From MaRDI portal
Publication:445032
DOI10.1016/j.automatica.2011.09.043zbMath1244.93178arXiv1105.4549OpenAlexW2080335539WikidataQ105583564 ScholiaQ105583564MaRDI QIDQ445032
Farzad Yousefian, Angelia Nedić, Uday V. Shanbhag
Publication date: 24 August 2012
Published in: Automatica (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1105.4549
stochastic optimizationconvex optimizationstochastic approximationadaptive steplengthrandomized smoothing techniques
Related Items
Almost sure convergence of the forward-backward-forward splitting algorithm, Accelerating mini-batch SARAH by step size rules, Stochastic forward-backward splitting for monotone inclusions, A stochastic successive minimization method for nonsmooth nonconvex optimization with applications to transceiver design in wireless communication networks, Descent direction method with line search for unconstrained optimization in noisy environment, ASTRO-DF: A Class of Adaptive Sampling Trust-Region Algorithms for Derivative-Free Stochastic Optimization, Stochastic mirror descent method for distributed multi-agent optimization, Incremental gradient-free method for nonsmooth distributed optimization, On smoothing, regularization, and averaging in stochastic approximation methods for stochastic variational inequality problems, A stochastic gradient method for a class of nonlinear PDE-constrained optimal control problems under uncertainty, Gradient-free federated learning methods with \(l_1\) and \(l_2\)-randomization for non-smooth convex stochastic optimization problems, Improved variance reduction extragradient method with line search for stochastic variational inequalities, An Improved Unconstrained Approach for Bilevel Optimization, Adaptive stochastic approximation algorithm, On Stochastic and Deterministic Quasi-Newton Methods for Nonstrongly Convex Optimization: Asymptotic Convergence and Rate Analysis, A stopping rule for stochastic approximation, Nonlinear Gradient Mappings and Stochastic Optimization: A General Framework with Applications to Heavy-Tail Noise, EFIX: exact fixed point methods for distributed optimization, Complexity guarantees for an implicit smoothing-enabled method for stochastic MPECs, On the computation of equilibria in monotone and potential stochastic hierarchical games, Technical Note—Consistency Analysis of Sequential Learning Under Approximate Bayesian Inference, Variance-Based Extragradient Methods with Line Search for Stochastic Variational Inequalities, String-averaging incremental stochastic subgradient algorithms, An incremental subgradient method on Riemannian manifolds, Convex optimization over fixed point sets of quasi-nonexpansive and nonexpansive mappings in utility-based bandwidth allocation problems with operational constraints, A Stochastic Quasi-Newton Method for Large-Scale Optimization, Non-cooperative games with minmax objectives, Stochastic generalized Nash equilibrium seeking under partial-decision information, The incremental subgradient methods on distributed estimations in-network, Perturbed iterate SGD for Lipschitz continuous loss functions, Smoothed Variable Sample-Size Accelerated Proximal Methods for Nonsmooth Stochastic Convex Programs
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Recourse-based stochastic nonlinear programming: properties and Benders-SQP algorithms
- Distributed stochastic subgradient projection algorithms for convex optimization
- A smoothing method for mathematical programs with equilibrium constraints
- Stochastic optimization problems with nondifferentiable cost functionals
- A Complementarity Framework for Forward Contracting Under Uncertainty
- Stochastic approximation method with gradient averaging for unconstrained problems
- Incremental Stochastic Subgradient Algorithms for Convex Optimization
- Decentralized Resource Allocation in Dynamic Networks of Agents
- Robust Stochastic Approximation Approach to Stochastic Programming
- Multivariate stochastic approximation using a simultaneous perturbation gradient approximation
- Acceleration of Stochastic Approximation by Averaging
- Introduction to Stochastic Programming
- Gradient Convergence in Gradient methods with Errors
- Smooth SQP Methods for Mathematical Programs with Nonlinear Complementarity Constraints
- Finite-Dimensional Variational Inequalities and Complementarity Problems
- The O.D.E. Method for Convergence of Stochastic Approximation and Reinforcement Learning
- Stochastic Approximation Approaches to the Stochastic Variational Inequality Problem
- Solving variational inequalities with Stochastic Mirror-Prox algorithm
- L-Shaped Linear Programs with Applications to Optimal Control and Stochastic Programming
- Stochastic Estimation of the Maximum of a Regression Function
- A Stochastic Approximation Method
- Probabilistic robust design with linear quadratic regulators
