Results 61 to 70 of about 19,550 (154)
An Extension of Subgradient Method for Variational Inequality Problems in Hilbert Space
Abstract and Applied Analysis, 2013 An extension of subgradient method for solving variational inequality problems is presented. A new iterative process, which relates to the fixed point of a nonexpansive mapping and the current iterative point, is generated.
Xueyong Wang, Shengjie Li, Xipeng Kou
doaj +1 more source
Learning in random utility models via online decision problems
International Journal of Economic Theory, Volume 21, Issue 4, Page 494-526, December 2025.Abstract This paper examines the Random Utility Model (RUM) in repeated stochastic choice settings where decision‐makers lack full information about payoffs. We propose a gradient‐based learning algorithm that embeds RUM into an online decision‐making framework.
Emerson Melo
wiley +1 more source
String-Averaging Projected Subgradient Methods for Constrained Minimization [PDF]
, 2013 We consider constrained minimization problems and propose to replace the projection onto the entire feasible region, required in the Projected Subgradient Method (PSM), by projections onto the individual sets whose intersection forms the entire feasible ...
Censor, Y., Zaslavski, A. J.
core
An Interior Projected-Like Subgradient Method for Mixed Variational Inequalities
Journal of Applied Mathematics, 2014 An interior projected-like subgradient method for mixed variational inequalities is proposed in finite dimensional spaces, which is based on using non-Euclidean projection-like operator. Under suitable assumptions, we prove that the sequence generated by
Guo-ji Tang, Xing Wang
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Robust design of flexible supply chains with mobile and modular facilities
AIChE Journal, Volume 71, Issue 11, November 2025.Abstract Modular manufacturing is increasingly being adopted by the chemical industry in applications where resource availability and product demand are highly distributed and uncertain. Modular plants are often built such that they can be easily relocated.
Congqin Ge, Zhihong Yuan, Qi Zhang
wiley +1 more source
Barrier subgradient method [PDF]
In this paper we develop a new primal-dual subgradient method for nonsmooth convex optimization problems. This scheme is based on a self-concordant barrier for the basic feasible set. It is suitable for finding approximate solutions with certain relative
NESTEROV, Y.
core
Derivatives with respect to metrics and applications: subgradient marching algorithm [PDF]
, 2018 This paper introduces a subgradient descent algorithm to compute a Riemannian metric that minimizes an energy involving geodesic distances. The heart of the method is the Subgradient Marching Algorithm to compute the derivative of the geodesic distance ...
Benmansour, F. +3 more
core
EURO Journal on Computational OptimizationWe introduce a heuristic rule for calculating the stepsize in the subgradient method for unconstrained convex nonsmooth optimization which, unlike the classic approach, is based on retaining some information from previous iteration.
F. Carrabs, M. Gaudioso, G. Miglionico
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Simultaneous Feature Selection for Optimal Dynamic Treatment Regimens
Statistics in Medicine, Volume 44, Issue 15-17, July 2025.ABSTRACT Dynamic treatment regimens (DTRs), where treatment decisions are tailored to individual patient's characteristics and evolving health status over multiple stages, have gained increasing interest in the modern era of precision medicine. Identifying important features that drive these decisions over stages not only leads to parsimonious DTRs for
Mochuan Liu, Yuanjia Wang, Donglin Zeng
wiley +1 more source
AlgorithmsIn this paper, we propose an incremental-type subgradient scheme for solving a nonsmooth convex–concave minimax optimization problem in the setting of Euclidean spaces.
Thipagon Feesantia +2 more
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