mlsanityData to 14 Oct 2026

Beyond L1: Faster and Better Sparse Models with skglm

arXiv 2204.07826 ↗First posted 16 Apr 2022stat.ML cs.LGcited by 16

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Abstract (arXiv)

We propose a new fast algorithm to estimate any sparse generalized linear model with convex or non-convex separable penalties. Our algorithm is able to solve problems with millions of samples and features in seconds, by relying on coordinate descent, working sets and Anderson acceleration. It handles previously unaddressed models, and is extensively shown to improve state-of-art algorithms. We provide a flexible, scikit-learn compatible package, which easily handles customized datafits and penalties.

Key facts. Cited by 16 papers in the map (data through 14 Oct 2026). Builds on 27 of its 87 references that are in the map. First posted on arXiv 16 Apr 2022.

Builds on

27 of 87 references.

References · 27

  1. 2018Stochastic model-based minimization of weakly convex functionscited by 159
  2. 2017Model Selection in Bayesian Neural Networks via Horseshoe Priorscited by 52
  3. 2015Coordinate Descent Converges Faster with the Gauss-Southwell Rule Than Random Selectioncited by 39
  4. 2016Gap Safe screening rules for sparsity enforcing penaltiescited by 39
  5. 2020Implicit differentiation of Lasso-type models for hyperparameter optimizationcited by 34
  6. 2015Mind the duality gap: safer rules for the Lassocited by 33
  7. 2018Celer: a Fast Solver for the Lasso with Dual Extrapolationcited by 31
  8. 2013Accelerated, Parallel and Proximal Coordinate Descentcited by 25
  9. 2018A Survey on Nonconvex Regularization Based Sparse and Low-Rank Recovery in Signal Processing, Statistics, and Machine Learningcited by 20
  10. 2016Regularized Nonlinear Accelerationcited by 18
  11. 2014Dynamic Screening: Accelerating First-Order Algorithms for the Lasso and Group-Lassocited by 11
  12. 2019Screening Rules for Lasso with Non-Convex Sparse Regularizerscited by 11
15 more
  1. 2019Anderson Acceleration of Proximal Gradient Methodscited by 9
  2. 2020Screening Rules and its Complexity for Active Set Identificationcited by 8
  3. 2021Stochastic Anderson Mixing for Nonconvex Stochastic Optimizationcited by 7
  4. 2019Trajectory of Alternating Direction Method of Multipliers and Adaptive Accelerationcited by 6
  5. 2020Anderson Acceleration for Nonconvex ADMM Based on Douglas-Rachford Splittingcited by 6
  6. 2020Anderson acceleration of coordinate descentcited by 6
  7. 2020Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Pythoncited by 5
  8. 2019Dual Extrapolation for Sparse Generalized Linear Modelscited by 4
  9. 2020Model identification and local linear convergence of coordinate descentcited by 4
  10. 2014Low Complexity Regularization of Linear Inverse Problemscited by 3
  11. 2016A Multi-step Inertial Forward--Backward Splitting Method for Non-convex Optimizationcited by 3
  12. 2018WHInter: A Working set algorithm for High-dimensional sparse second order Interaction modelscited by 3
  13. 2019Efficiency of Coordinate Descent Methods For Structured Nonconvex Optimizationcited by 3
  14. 2021Continuation Path with Linear Convergence Ratecited by 3
  15. 2016The iterative reweighted Mixed-Norm Estimate for spatio-temporal MEG/EEG source reconstructioncited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 1; 2023: 3; 2024: 2; 2025: 7; 2026: 3.

16 papers.

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  1. 2022Benchopt: Reproducible, efficient and collaborative optimization benchmarkscited by 27
  2. 2023Conformalization of Sparse Generalized Linear Modelscited by 4
  3. 2023Anderson Acceleration For Bioinformatics-Based Machine Learningcited by 2
  4. 2023FedECA: Federated External Control Arms for Causal Inference with Time-To-Event Data in Distributed Settingscited by 2
  5. 2024Integrated path stability selectioncited by 2
  6. 2025The Choice of Normalization Influences Shrinkage in Regularized Regressioncited by 2
  7. 2024FastSurvival: Hidden Computational Blessings in Training Cox Proportional Hazards Modelscited by 1
  8. 2025Scalable Approximate Algorithms for Optimal Transport Linear Modelscited by 0
  9. 2025A Generic Branch-and-Bound Algorithm for ℓ0-Penalized Problems with Supplementary Materialcited by 0
  10. 2025El0ps: An Exact L0-regularized Problems Solvercited by 0
  11. 2025Proximal Operators of Sorted Nonconvex Penaltiescited by 0
  12. 2025SigBERT: Combining Narrative Medical Reports and Rough Path Signature Theory for Survival Risk Estimation in Oncologycited by 0
4 more
  1. 2025Efficient Solvers for SLOPE in R, Python, Julia, and C++cited by 0
  2. 2026A Flexible Empirical Bayes Approach to Generalized Linear Models, with Applications to Sparse Logistic Regressioncited by 0
  3. 2026A block-coordinate descent framework for non-convex composite optimization. Application to sparse precision matrix estimationcited by 0
  4. 2026Simpler Methods Work Better for L1 Penalized Logistic Models and Large Datasetscited by 0