Homogeneous self-dual algorithms for stochastic semidefinite programming

DOI10.1007/s10957-012-0110-xzbMath1277.90092OpenAlexW2109129402MaRDI QIDQ1935265

Yanyan Li

Publication date: 14 February 2013

Published in: Journal of Optimization Theory and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10957-012-0110-x

zbMATH Keywords

semidefinite programminginterior point methods

Mathematics Subject Classification ID

Semidefinite programming (90C22) Stochastic programming (90C15)

Related Items (5)

Inexact SA method for constrained stochastic convex SDP and application in Chinese stock market ⋮ Unnamed Item ⋮ Homogeneous self-dual algorithms for stochastic second-order cone programming ⋮ On risk-averse stochastic semidefinite programs with continuous recourse ⋮ Quantitative stability of two-stage distributionally robust risk optimization problem with full random linear semi-definite recourse

Uses Software

• SDPHA
• SDPT3

Cites Work

• Stochastic semidefinite programming: a new paradigm for stochastic optimization
• A class of polynomial volumetric barrier decomposition algorithms for stochastic semidefinite programming
• Semidefinite optimization
• On the Nesterov--Todd Direction in Semidefinite Programming
• On homogeneous interrior-point algorithms for semidefinite programming
• SDPT3 — A Matlab software package for semidefinite programming, Version 1.3

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