Mirror descent and convex optimization problems with non-smooth inequality constraints
From MaRDI portal
Publication:2415205
DOI10.1007/978-3-319-97478-1_8zbMath1421.90112arXiv1710.06612OpenAlexW2767083550MaRDI QIDQ2415205
Fedor S. Stonyakin, Anastasia Bayandina, Pavel Dvurechensky, Alexander V. Gasnikov, Alexander A. Titov
Publication date: 21 May 2019
Full work available at URL: https://arxiv.org/abs/1710.06612
primal-dual methodsrestartsadaptive stepsizeadaptive stopping ruleconstrained non-smooth convex optimizationstochastic adaptive mirror descent
Convex programming (90C25) Large-scale problems in mathematical programming (90C06) Nonlinear programming (90C30) Complexity and performance of numerical algorithms (65Y20)
Related Items
Complexity of an inexact proximal-point penalty method for constrained smooth non-convex optimization, Generalized mirror prox algorithm for monotone variational inequalities: Universality and inexact oracle, Stochastic saddle-point optimization for the Wasserstein barycenter problem, Composite optimization for the resource allocation problem, Adaptive subgradient methods for mathematical programming problems with quasiconvex functions, First-order methods for convex optimization, Recent theoretical advances in decentralized distributed convex optimization, Alternating minimization methods for strongly convex optimization, An accelerated directional derivative method for smooth stochastic convex optimization, Analogues of Switching Subgradient Schemes for Relatively Lipschitz-Continuous Convex Programming Problems, Adaptive Mirror Descent Algorithms for Convex and Strongly Convex Optimization Problems with Functional Constraints, On Modification of an Adaptive Stochastic Mirror Descent Algorithm for Convex Optimization Problems with Functional Constraints
