An interior proximal gradient method for nonconvex optimization

Cites Work

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Interior point methods 25 years later
A new polynomial-time algorithm for linear programming
An interior-point algorithm for nonconvex nonlinear programming
Simple algorithms for optimization on Riemannian manifolds with constraints
Convergence properties of monotone and nonmonotone proximal gradient methods revisited
Block-coordinate and incremental aggregated proximal gradient methods for nonsmooth nonconvex problems
Proximal gradient algorithms under local Lipschitz gradient continuity. A convergence and robustness analysis of PANOC
A proximal interior point algorithm with applications to image processing
A mixed logarithmic barrier-augmented Lagrangian method for nonlinear optimization
A penalty-interior-point algorithm for nonlinear constrained optimization
On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming
Non-Negative Principal Component Analysis: Message Passing Algorithms and Sharp Asymptotics
On projected newton barrier methods for linear programming and an equivalence to Karmarkar’s projective method
Variational Analysis
Regularized symmetric indefinite systems in interior point methods for linear and quadratic optimization
Variational Analysis and Applications
First Order Methods Beyond Convexity and Lipschitz Gradient Continuity with Applications to Quadratic Inverse Problems
Forward-Backward Envelope for the Sum of Two Nonconvex Functions: Further Properties and Nonmonotone Linesearch Algorithms
Relatively Smooth Convex Optimization by First-Order Methods, and Applications
FOM – a MATLAB toolbox of first-order methods for solving convex optimization problems
Interior Methods for Nonlinear Optimization
The interior-point revolution in optimization: History, recent developments, and lasting consequences
An ADMM-based interior-point method for large-scale linear programming
Interior-proximal primal-dual methods
Benchmarking Derivative-Free Optimization Algorithms
The Variable Metric Forward-Backward Splitting Algorithm Under Mild Differentiability Assumptions
Practical Augmented Lagrangian Methods for Constrained Optimization
A Bregman Forward-Backward Linesearch Algorithm for Nonconvex Composite Optimization: Superlinear Convergence to Nonisolated Local Minima
Bregman Finito/MISO for Nonconvex Regularized Finite Sum Minimization without Lipschitz Gradient Continuity
Constrained composite optimization and augmented Lagrangian methods
A Bregman inertial forward-reflected-backward method for nonconvex minimization
Riemannian Interior Point Methods for Constrained Optimization on Manifolds
SPIRAL: a superlinearly convergent incremental proximal algorithm for nonconvex finite sum minimization
Proximal gradient methods beyond monotony

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