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Celer: a Fast Solver for the Lasso with Dual Extrapolation
v1v2v3 (latest)

Celer: a Fast Solver for the Lasso with Dual Extrapolation

21 February 2018
Mathurin Massias
Alexandre Gramfort
Joseph Salmon
ArXiv (abs)PDFHTML

Papers citing "Celer: a Fast Solver for the Lasso with Dual Extrapolation"

47 / 47 papers shown
Efficient Solvers for SLOPE in R, Python, Julia, and C++
Efficient Solvers for SLOPE in R, Python, Julia, and C++
Johan Larsson
Malgorzata Bogdan
Krystyna Grzesiak
Mathurin Massias
J. Wallin
234
0
0
04 Nov 2025
Enhanced Cyclic Coordinate Descent Methods for Elastic Net Penalized Linear Models
Enhanced Cyclic Coordinate Descent Methods for Elastic Net Penalized Linear Models
Yixiao Wang
Zishan Shao
Ting Jiang
Aditya Devarakonda
134
0
0
22 Oct 2025
High Dimensional Bayesian Optimization using Lasso Variable Selection
High Dimensional Bayesian Optimization using Lasso Variable SelectionInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2025
Vu Viet Hoang
Hung The Tran
Sunil R. Gupta
Vu Nguyen
410
0
0
02 Apr 2025
Representational Similarity via Interpretable Visual Concepts
Representational Similarity via Interpretable Visual ConceptsInternational Conference on Learning Representations (ICLR), 2025
Neehar Kondapaneni
Oisin Mac Aodha
Pietro Perona
DRL
1.1K
5
0
19 Mar 2025
Efficient Low-rank Identification via Accelerated Iteratively Reweighted
  Nuclear Norm Minimization
Efficient Low-rank Identification via Accelerated Iteratively Reweighted Nuclear Norm Minimization
Hao Wang
Ye Wang
Xiangyu Yang
346
0
0
22 Jun 2024
Efficient Algorithms for Regularized Nonnegative Scale-invariant Low-rank Approximation Models
Efficient Algorithms for Regularized Nonnegative Scale-invariant Low-rank Approximation Models
Jeremy E. Cohen
Valentin Leplat
615
6
0
27 Mar 2024
Dynamic Incremental Optimization for Best Subset Selection
Dynamic Incremental Optimization for Best Subset Selection
Shaogang Ren
Xiaoning Qian
372
0
0
04 Feb 2024
Anytime Model Selection in Linear Bandits
Anytime Model Selection in Linear BanditsNeural Information Processing Systems (NeurIPS), 2023
Parnian Kassraie
N. Emmenegger
Andreas Krause
Aldo Pacchiano
409
7
0
24 Jul 2023
Safe Screening for Unbalanced Optimal Transport
Safe Screening for Unbalanced Optimal Transport
Xun Su
Zhongxi Fang
Hiroyuki Kasai
OT
329
0
0
01 Jul 2023
Lifelong Bandit Optimization: No Prior and No Regret
Lifelong Bandit Optimization: No Prior and No RegretConference on Uncertainty in Artificial Intelligence (UAI), 2022
Felix Schur
Parnian Kassraie
Jonas Rothfuss
Andreas Krause
407
3
0
27 Oct 2022
Best Subset Selection with Efficient Primal-Dual Algorithm
Best Subset Selection with Efficient Primal-Dual Algorithm
Shaogang Ren
Guanhua Fang
P. Li
152
1
0
05 Jul 2022
Benchopt: Reproducible, efficient and collaborative optimization
  benchmarks
Benchopt: Reproducible, efficient and collaborative optimization benchmarksNeural Information Processing Systems (NeurIPS), 2022
Thomas Moreau
Mathurin Massias
Alexandre Gramfort
Pierre Ablin
Pierre-Antoine Bannier Benjamin Charlier
...
Binh Duc Nguyen
A. Rakotomamonjy
Zaccharie Ramzi
Joseph Salmon
Samuel Vaiter
404
49
0
27 Jun 2022
Smooth over-parameterized solvers for non-smooth structured optimization
Smooth over-parameterized solvers for non-smooth structured optimizationMathematical programming (Math. Program.), 2022
C. Poon
Gabriel Peyré
332
23
0
03 May 2022
Hybrid ISTA: Unfolding ISTA With Convergence Guarantees Using Free-Form
  Deep Neural Networks
Hybrid ISTA: Unfolding ISTA With Convergence Guarantees Using Free-Form Deep Neural NetworksIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022
Ziyang Zheng
Wenrui Dai
Duoduo Xue
Chenglin Li
Junni Zou
H. Xiong
333
24
0
25 Apr 2022
Beyond L1: Faster and Better Sparse Models with skglm
Beyond L1: Faster and Better Sparse Models with skglmNeural Information Processing Systems (NeurIPS), 2022
Quentin Bertrand
Quentin Klopfenstein
Pierre-Antoine Bannier
Gauthier Gidel
Mathurin Massias
333
29
0
16 Apr 2022
Datamodels: Predicting Predictions from Training Data
Datamodels: Predicting Predictions from Training Data
Andrew Ilyas
Sung Min Park
Logan Engstrom
Guillaume Leclerc
Aleksander Madry
TDI
478
191
0
01 Feb 2022
Meta-Learning Hypothesis Spaces for Sequential Decision-making
Meta-Learning Hypothesis Spaces for Sequential Decision-makingInternational Conference on Machine Learning (ICML), 2022
Parnian Kassraie
Jonas Rothfuss
Andreas Krause
OffRL
526
6
0
01 Feb 2022
Continuation Path with Linear Convergence Rate
Continuation Path with Linear Convergence Rate
Eugène Ndiaye
Ichiro Takeuchi
269
4
0
09 Dec 2021
OmiTrans: generative adversarial networks based omics-to-omics
  translation framework
OmiTrans: generative adversarial networks based omics-to-omics translation frameworkIEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2021
Xiaoyu Zhang
Wenhan Luo
MedIm
407
6
0
27 Nov 2021
LassoBench: A High-Dimensional Hyperparameter Optimization Benchmark
  Suite for Lasso
LassoBench: A High-Dimensional Hyperparameter Optimization Benchmark Suite for Lasso
Kenan Sehic
Alexandre Gramfort
Joseph Salmon
Luigi Nardi
420
50
0
04 Nov 2021
Differentially Private Coordinate Descent for Composite Empirical Risk
  Minimization
Differentially Private Coordinate Descent for Composite Empirical Risk MinimizationInternational Conference on Machine Learning (ICML), 2021
Paul Mangold
A. Bellet
Joseph Salmon
Marc Tommasi
600
16
0
22 Oct 2021
abess: A Fast Best Subset Selection Library in Python and R
abess: A Fast Best Subset Selection Library in Python and R
Jin Zhu
Xueqin Wang
Liyuan Hu
Junhao Huang
Kangkang Jiang
Yanhang Zhang
Shiyun Lin
Junxian Zhu
286
32
0
19 Oct 2021
yaglm: a Python package for fitting and tuning generalized linear models
  that supports structured, adaptive and non-convex penalties
yaglm: a Python package for fitting and tuning generalized linear models that supports structured, adaptive and non-convex penalties
Iain Carmichael
T. Keefe
Naomi Giertych
Jonathan P. Williams
205
2
0
11 Oct 2021
Unbalanced Optimal Transport through Non-negative Penalized Linear
  Regression
Unbalanced Optimal Transport through Non-negative Penalized Linear RegressionNeural Information Processing Systems (NeurIPS), 2021
Laetitia Chapel
Rémi Flamary
Haoran Wu
Cédric Févotte
Gilles Gasso
OT
215
57
0
08 Jun 2021
Smooth Bilevel Programming for Sparse Regularization
Smooth Bilevel Programming for Sparse RegularizationNeural Information Processing Systems (NeurIPS), 2021
C. Poon
Gabriel Peyré
338
21
0
02 Jun 2021
Implicit differentiation for fast hyperparameter selection in non-smooth
  convex learning
Implicit differentiation for fast hyperparameter selection in non-smooth convex learningJournal of machine learning research (JMLR), 2021
Quentin Bertrand
Quentin Klopfenstein
Mathurin Massias
Mathieu Blondel
Samuel Vaiter
Alexandre Gramfort
Joseph Salmon
363
33
0
04 May 2021
The Hessian Screening Rule
The Hessian Screening RuleNeural Information Processing Systems (NeurIPS), 2021
Johan Larsson
J. Wallin
327
4
0
27 Apr 2021
Elastic Net Regularization Paths for All Generalized Linear Models
Elastic Net Regularization Paths for All Generalized Linear ModelsJournal of Statistical Software (JSS), 2021
J. K. Tay
B. Narasimhan
Trevor Hastie
121
496
0
05 Mar 2021
Anderson acceleration of coordinate descent
Anderson acceleration of coordinate descentInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2020
Quentin Bertrand
Mathurin Massias
419
17
0
19 Nov 2020
Model identification and local linear convergence of coordinate descent
Model identification and local linear convergence of coordinate descent
Quentin Klopfenstein
Quentin Bertrand
Alexandre Gramfort
Joseph Salmon
Samuel Vaiter
329
5
0
22 Oct 2020
Nonsmoothness in Machine Learning: specific structure, proximal
  identification, and applications
Nonsmoothness in Machine Learning: specific structure, proximal identification, and applicationsSet-Valued and Variational Analysis (SVVA), 2020
F. Iutzeler
J. Malick
321
19
0
02 Oct 2020
Statistical control for spatio-temporal MEG/EEG source imaging with
  desparsified multi-task Lasso
Statistical control for spatio-temporal MEG/EEG source imaging with desparsified multi-task Lasso
Jérôme-Alexis Chevalier
Alexandre Gramfort
Joseph Salmon
Bertrand Thirion
465
10
0
29 Sep 2020
Screening Rules and its Complexity for Active Set Identification
Screening Rules and its Complexity for Active Set Identification
Eugène Ndiaye
Olivier Fercoq
Joseph Salmon
257
9
0
06 Sep 2020
Provably Convergent Working Set Algorithm for Non-Convex Regularized
  Regression
Provably Convergent Working Set Algorithm for Non-Convex Regularized RegressionInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2020
A. Rakotomamonjy
Rémi Flamary
Gilles Gasso
Joseph Salmon
329
6
0
24 Jun 2020
An Efficient Semi-smooth Newton Augmented Lagrangian Method for Elastic
  Net
An Efficient Semi-smooth Newton Augmented Lagrangian Method for Elastic Net
Tobia Boschi
M. Reimherr
Francesca Chiaromonte
219
3
0
06 Jun 2020
Implicit differentiation of Lasso-type models for hyperparameter
  optimization
Implicit differentiation of Lasso-type models for hyperparameter optimizationInternational Conference on Machine Learning (ICML), 2020
Quentin Bertrand
Quentin Klopfenstein
Mathieu Blondel
Samuel Vaiter
Alexandre Gramfort
Joseph Salmon
423
72
0
20 Feb 2020
On Newton Screening
Jian Huang
Yuling Jiao
Lican Kang
Jin Liu
Yanyan Liu
Xiliang Lu
Yuanyuan Yang
347
2
0
27 Jan 2020
Anderson Acceleration of Proximal Gradient Methods
Anderson Acceleration of Proximal Gradient MethodsInternational Conference on Machine Learning (ICML), 2019
Vien V. Mai
M. Johansson
186
44
0
18 Oct 2019
Dual Extrapolation for Sparse Generalized Linear Models
Dual Extrapolation for Sparse Generalized Linear Models
Mathurin Massias
Samuel Vaiter
Alexandre Gramfort
Joseph Salmon
1.0K
19
0
12 Jul 2019
Large scale Lasso with windowed active set for convolutional spike
  sorting
Large scale Lasso with windowed active set for convolutional spike sorting
Laurent Dragoni
Rémi Flamary
Karim Lounici
Patricia Reynaud-Bouret
228
0
0
28 Jun 2019
Learning step sizes for unfolded sparse coding
Learning step sizes for unfolded sparse codingNeural Information Processing Systems (NeurIPS), 2019
Pierre Ablin
Thomas Moreau
Mathurin Massias
Alexandre Gramfort
MQ
281
60
0
27 May 2019
Screening Rules for Lasso with Non-Convex Sparse Regularizers
Screening Rules for Lasso with Non-Convex Sparse Regularizers
A. Rakotomamonjy
Gilles Gasso
Joseph Salmon
272
25
0
16 Feb 2019
Handling correlated and repeated measurements with the smoothed
  multivariate square-root Lasso
Handling correlated and repeated measurements with the smoothed multivariate square-root Lasso
Quentin Bertrand
Mathurin Massias
Alexandre Gramfort
Joseph Salmon
427
0
0
07 Feb 2019
Stable safe screening and structured dictionaries for faster L1
  regularization
Stable safe screening and structured dictionaries for faster L1 regularization
C. Dantas
Rémi Gribonval
332
6
0
17 Dec 2018
Efficient Greedy Coordinate Descent for Composite Problems
Efficient Greedy Coordinate Descent for Composite Problems
Sai Praneeth Karimireddy
Anastasia Koloskova
Sebastian U. Stich
Martin Jaggi
176
31
0
16 Oct 2018
A Fast, Principled Working Set Algorithm for Exploiting Piecewise Linear
  Structure in Convex Problems
A Fast, Principled Working Set Algorithm for Exploiting Piecewise Linear Structure in Convex Problems
Tyler B. Johnson
Carlos Guestrin
219
5
0
20 Jul 2018
Scaling Up Sparse Support Vector Machines by Simultaneous Feature and
  Sample Reduction
Scaling Up Sparse Support Vector Machines by Simultaneous Feature and Sample Reduction
Weizhong Zhang
Bin Hong
Wei Liu
Jieping Ye
Deng Cai
Xiaofei He
Jie Wang
308
40
0
24 Jul 2016
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