Techniques for accelerating branch-and-bound algorithms dedicated to sparse optimization
From MaRDI portal
Publication:6585819
DOI10.1080/10556788.2023.2241154MaRDI QIDQ6585819
Jordan Ninin, Sébastien Bourguignon, Unnamed Author
Publication date: 12 August 2024
Published in: Optimization Methods \& Software (Search for Journal in Brave)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Best subset selection via a modern optimization lens
- Algorithm for cardinality-constrained quadratic optimization
- Computational study of a family of mixed-integer quadratic programming problems
- Least angle regression. (With discussion)
- A first-order primal-dual algorithm for convex problems with applications to imaging
- Sparse regression at scale: branch-and-bound rooted in first-order optimization
- Sparse regression: scalable algorithms and empirical performance
- Convex relaxations and MIQCQP reformulations for a class of cardinality-constrained portfolio selection problems
- Atomic Decomposition by Basis Pursuit
- Optimization with Sparsity-Inducing Penalties
- An algorithm for quadratic ℓ1-regularized optimization with a flexible active-set strategy
- Lagrangian relaxation procedure for cardinality-constrained portfolio optimization
- Greed is Good: Algorithmic Results for Sparse Approximation
- Maximum likelihood detection and estimation of Bernoulli - Gaussian processes
- A new approach to variable selection in least squares problems
- From Bernoulli–Gaussian Deconvolution to Sparse Signal Restoration
- Exact Sparse Approximation Problems via Mixed-Integer Programming: Formulations and Computational Performance
- Gap Safe screening rules for sparsity enforcing penalties
- An iterative thresholding algorithm for linear inverse problems with a sparsity constraint
- Analysis of multiresolution image denoising schemes using generalized Gaussian and complexity priors
- Sparse Approximate Solutions to Linear Systems
- Sharp Thresholds for High-Dimensional and Noisy Sparsity Recovery Using $\ell _{1}$-Constrained Quadratic Programming (Lasso)
- Global optimization for sparse solution of least squares problems
- A Unified View of Exact Continuous Penalties for $\ell_2$-$\ell_0$ Minimization
- Convex Analysis
- Strong Rules for Discarding Predictors in Lasso-Type Problems
- Convex analysis and monotone operator theory in Hilbert spaces
- The elements of statistical learning. Data mining, inference, and prediction
- Convergence of a block coordinate descent method for nondifferentiable minimization
- Benchmarking optimization software with performance profiles.
This page was built for publication: Techniques for accelerating branch-and-bound algorithms dedicated to sparse optimization