Linearly convergent bilevel optimization with single-step inner methods
From MaRDI portal
Publication:6155063
DOI10.1007/s10589-023-00527-7arXiv2205.04862OpenAlexW4387131582MaRDI QIDQ6155063
Ensio Suonperä, Tuomo Valkonen
Publication date: 16 February 2024
Published in: Computational Optimization and Applications (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2205.04862
Cites Work
- Unnamed Item
- Unnamed Item
- Bilevel optimization for calibrating point spread functions in blind deconvolution
- Solving ill-posed bilevel programs
- Techniques for gradient-based bilevel optimization with non-smooth lower level problems
- Bilevel parameter learning for higher-order total variation regularisation models
- The structure of optimal parameters for image restoration problems
- Optimal selection of the regularization function in a weighted total variation model. II: Algorithm, its analysis and numerical tests
- Generalized Nash equilibrium problems, bilevel programming and MPEC. Based on lectures given at the international center for pure and applied mathematics (CIMPA) school, Delhi, India, November 25 -- December 6, 2013
- On bilevel programming. I: General nonlinear cases
- A first-order primal-dual algorithm for convex problems with applications to imaging
- Solving bilevel programs with the KKT-approach
- The bilevel programming problem: reformulations, constraint qualifications and optimality conditions
- Gauss-Newton-type methods for bilevel optimization
- Inexact derivative-free optimization for bilevel learning
- Testing and non-linear preconditioning of the proximal point method
- Application of particle swarm optimization based on CHKS smoothing function for solving nonlinear bilevel programming problem
- Image denoising: learning the noise model via nonsmooth PDE-constrained optimization
- A Bilevel Optimization Approach for Parameter Learning in Variational Models
- Convergence Analysis of Primal-Dual Algorithms for a Saddle-Point Problem: From Contraction Perspective
- Dynamic Sampling Schemes for Optimal Noise Learning Under Multiple Nonsmooth Constraints
- Bi-CGSTAB: A Fast and Smoothly Converging Variant of Bi-CG for the Solution of Nonsymmetric Linear Systems
- Acceleration and Global Convergence of a First-Order Primal-Dual Method for Nonconvex Problems
- A bilevel approach for parameter learning in inverse problems
- Optimality conditions for bilevel programming problems
- A primal–dual hybrid gradient method for nonlinear operators with applications to MRI
- Sufficient Optimality Conditions in Bilevel Programming
- Optimality Conditions for Bilevel Imaging Learning Problems with Total Variation Regularization
- Directional Necessary Optimality Conditions for Bilevel Programs
- Bilevel Programming Problems
- A First Order Method for Solving Convex Bilevel Optimization Problems
- An inertial extrapolation method for convex simple bilevel optimization
- Learning Consistent Discretizations of the Total Variation
- Mathematical Programs with Equilibrium Constraints
This page was built for publication: Linearly convergent bilevel optimization with single-step inner methods