Hessian Barrier Algorithms for Linearly Constrained Optimization Problems-Reference-Cited by-同舟云学术

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Hessian Barrier Algorithms for Linearly Constrained Optimization Problems

Published:2019-01 Issue:3 Volume:29 Page:2100-2127
ISSN:1052-6234
Container-title:SIAM Journal on Optimization
language:en
Short-container-title:SIAM J. Optim.

Author:

Bomze Immanuel M.,Mertikopoulos Panayotis^ORCID,Schachinger Werner,Staudigl Mathias^ORCID

Funder

Agence Nationale de la Recherche

European Cooperation in Science and Technology

Publisher

Society for Industrial & Applied Mathematics (SIAM)

Subject

Theoretical Computer Science,Software

Link

https://epubs.siam.org/doi/pdf/10.1137/18M1215682

Reference44 articles.

1. Hessian Riemannian Gradient Flows in Convex Programming

2. Singular Riemannian barrier methods and gradient-projection dynamical systems for constrained optimization

3. Convergence of descent methods for semi-algebraic and tame problems: proximal algorithms, forward–backward splitting, and regularized Gauss–Seidel methods

4. THE HEAVY BALL WITH FRICTION METHOD, I. THE CONTINUOUS DYNAMICAL SYSTEM: GLOBAL EXPLORATION OF THE LOCAL MINIMA OF A REAL-VALUED FUNCTION BY ASYMPTOTIC ANALYSIS OF A DISSIPATIVE DYNAMICAL SYSTEM

5. The Rate of Convergence of Nesterov's Accelerated Forward-Backward Method is Actually Faster Than $1/k^2$

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1. Hessian barrier algorithms for non-convex conic optimization;Mathematical Programming;2024-03-04

2. A Geodesic Interior-Point Method for Linear Optimization over Symmetric Cones;SIAM Journal on Optimization;2023-06-22

3. Generalized self-concordant analysis of Frank–Wolfe algorithms;Mathematical Programming;2022-01-29

4. First-Order Methods for Convex Optimization;EURO Journal on Computational Optimization;2021

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