Nonlinear rescaling as interior quadratic prox method in convex optimization
From MaRDI portal
Publication:861517
DOI10.1007/s10589-006-9759-0zbMath1128.90047OpenAlexW2011766928MaRDI QIDQ861517
Publication date: 29 January 2007
Published in: Computational Optimization and Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10589-006-9759-0
Related Items (4)
Modified Lagrangian methods for separable optimization problems ⋮ Primal–dual exterior point method for convex optimization ⋮ Unnamed Item ⋮ Lagrangian transformation and interior ellipsoid methods in convex optimization
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- On the convergence of the exponential multiplier method for convex programming
- Primal-dual nonlinear rescaling method for convex optimization
- Modified barrier functions (theory and methods)
- An interior-point algorithm for nonconvex nonlinear programming
- Nonlinear rescaling and proximal-like methods in convex optimization
- Nonlinear rescaling vs. smoothing technique in convex optimization
- Computational experience with penalty-barrier methods for nonlinear programming
- The Newton modified barrier method for QP problems
- Multiplier and gradient methods
- On the Convergence of the Proximal Point Algorithm for Convex Minimization
- Monotone Operators and the Proximal Point Algorithm
- Augmented Lagrangians and Applications of the Proximal Point Algorithm in Convex Programming
- Asymptotic Analysis for Penalty and Barrier Methods in Convex and Linear Programming
- Penalty/Barrier Multiplier Methods for Convex Programming Problems
- A dual approach to solving nonlinear programming problems by unconstrained optimization
- Interior Proximal and Multiplier Methods Based on Second Order Homogeneous Kernels
- Proximité et dualité dans un espace hilbertien
- Log-sigmoid multipliers method in constrained optimization
This page was built for publication: Nonlinear rescaling as interior quadratic prox method in convex optimization