A stochastic trust region method for unconstrained optimization problems

DOI10.1155/2019/8095054zbMath1435.90094OpenAlexW2913386018MaRDI QIDQ2298821

Dan Xue, Ningning Li, Jing Wang, Wen-Yu Sun

Publication date: 20 February 2020

Published in: Mathematical Problems in Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2019/8095054

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonconvex programming, global optimization (90C26) Stochastic programming (90C15) Methods of successive quadratic programming type (90C55)

Uses Software

• Pegasos

Cites Work

• Minimizing finite sums with the stochastic average gradient
• Optimization theory and methods. Nonlinear programming
• Large-Scale Machine Learning with Stochastic Gradient Descent
• Global Convergence of a a of Trust-Region Methods for Nonconvex Minimization in Hilbert Space
• Robust Stochastic Approximation Approach to Stochastic Programming
• A Trust Region Algorithm for Nonlinearly Constrained Optimization
• Numerical Optimization
• Ergodic Stochastic Optimization Algorithms for Wireless Communication and Networking
• RES: Regularized Stochastic BFGS Algorithm
• On‐line learning for very large data sets

This page was built for publication: A stochastic trust region method for unconstrained optimization problems