Central paths in semidefinite programming, generalized proximal-point method and Cauchy trajectories in Riemannian manifolds
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Publication:1014028
DOI10.1007/s10957-008-9422-2zbMath1194.90068OpenAlexW1981652825WikidataQ115382589 ScholiaQ115382589MaRDI QIDQ1014028
R. C. M. Silva, João Xavier da Cruz Neto, Paulo Roberto Oliveira, Orizon P. Ferreira
Publication date: 24 April 2009
Published in: Journal of Optimization Theory and Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10957-008-9422-2
semidefinite programmingRiemannian manifoldscentral pathCauchy trajectorygeneralized proximal-point methods
Related Items (5)
On the central paths in symmetric cone programming ⋮ Unnamed Item ⋮ An incremental subgradient method on Riemannian manifolds ⋮ Interior proximal methods and central paths for convex second-order cone programming ⋮ A new barrier for a class of semidefinite problems
Cites Work
- Unnamed Item
- Smooth nonlinear optimization of \(\mathbb R^n\)
- On some properties of generalized proximal point methods for variational inequalities
- A class of polynomial variable metric algorithms for linear optimization
- On the Riemannian geometry defined by self-concordant barriers and interior-point methods.
- Multi-Parameter Surfaces of Analytic Centers and Long-Step Surface-Following Interior Point Methods
- Convergence Analysis of a Proximal-Like Minimization Algorithm Using Bregman Functions
- Semidefinite optimization
- Monotone Operators and the Proximal Point Algorithm
- An Interior Proximal Algorithm and the Exponential Multiplier Method for Semidefinite Programming
- Central Paths, Generalized Proximal Point Methods, and Cauchy Trajectories in Riemannian Manifolds
- THE CENTRAL PATH IN SMOOTH CONVEX SEMIDEFINITE PROGRAMS
- Proximal Point Algorithm On Riemannian Manifolds
- Hessian Riemannian Gradient Flows in Convex Programming
- Nonlinear Proximal Point Algorithms Using Bregman Functions, with Applications to Convex Programming
- Interior Point Methods in Semidefinite Programming with Applications to Combinatorial Optimization
- On the Convergence of the Central Path in Semidefinite Optimization
- Limiting behavior of the central path in semidefinite optimization
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