An Interior-Point Method for Large-Scale ℓ_1-Regularized Least Squares
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- Type
- article
- Published
- 2007-12-01
- Cited by
- 1,885
- References
- 62
- OpenAlex
- https://openalex.org/W3022380717
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:675041
Keywords
Compressed sensing, Interior point method, Basis pursuit, Lasso (programming language), Algorithm
References
- Iterative methods for sparse linear systems
- Convex Analysis And Nonlinear Optimization
- Review of 'Numerical Optimization' by Bonnans, Gilbert, Lemaréchal and Sagastizabal
- Primal-Dual Interior-Point Methods
- Sharp thresholds for high-dimensional and noisy recovery of sparsity
- Introduction to optimization
- Applied Numerical Linear Algebra
- Statistical inference under order restrictions : the theory and application of isotonic regression
- Asymptotics for lasso-type estimators
- Extensions of compressed sensing
- Atomic Decomposition by Basis Pursuit
- Addendum: Regularization and variable selection via the elastic net
- High-dimensional graphs and variable selection with the Lasso
- An Iterative Regularization Method for Total Variation-Based Image Restoration
- Solving Ill-Conditioned and Singular Linear Systems: A Tutorial on Regularization
- The Adaptive Lasso and Its Oracle Properties
- A truncated primal‐infeasible dual‐feasible network interior point method
- PATHWISE COORDINATE OPTIMIZATION
- A new approach to variable selection in least squares problems
- The Elements of Statistical Learning
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- Removing camera shake blur and unwanted occluders from photographs. (Restauration des images par l'élimination du flou et des occlusions)
- Algorithmes d'ensemble actif pour le LASSO
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- A Comparison of Optimization Methods and Software for Large-scale L1-regularized Linear Classification
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