The Lasso Problem and Uniqueness

1 June 2012

Papers citing "The Lasso Problem and Uniqueness"

50 / 158 papers shown

Title
Explainable Neural Networks with Guarantees: A Sparse Estimation Approach Antoine Ledent Peng Liu FAtt 109 0 0 20 Feb 2025
Learning Massive-scale Partial Correlation Networks in Clinical Multi-omics Studies with HP-ACCORD Sungdong Lee Joshua Bang Youngrae Kim Hyungwon Choi Sang-Yun Oh Joong-Ho Won 61 0 0 16 Dec 2024
A Fast Coordinate Descent Method for High-Dimensional Non-Negative Least Squares using a Unified Sparse Regression Framework James Yang Trevor Hastie 23 0 0 03 Oct 2024
The Geometry and Well-Posedness of Sparse Regularized Linear Regression J. M. Everink Yiqiu Dong Martin Skovgaard Andersen 16 1 0 05 Sep 2024
Controlled Learning of Pointwise Nonlinearities in Neural-Network-Like Architectures Michael Unser Alexis Goujon Stanislas Ducotterd 31 2 0 23 Aug 2024
Geometric Approach and Closed Exact Formulae for the Lasso Vladimir Dragović Borislav Gajić 26 0 0 10 Jul 2024
Randomized Geometric Algebra Methods for Convex Neural Networks Yifei Wang Sungyoon Kim Paul Chu Indu Subramaniam Mert Pilanci AAML 50 0 0 04 Jun 2024
Efficient Algorithms for Regularized Nonnegative Scale-invariant Low-rank Approximation Models Jeremy E. Cohen Valentin Leplat 63 1 0 27 Mar 2024
On Minimum Trace Factor Analysis -- An Old Song Sung to a New Tune C. Li A. Shkolnik 13 0 0 04 Feb 2024
A Comparative Analysis of Gene Expression Profiling by Statistical and Machine Learning Approaches Myriam Bontonou Anais Haget Maria Boulougouri Benjamin Audit Pierre Borgnat J. Arbona 22 0 0 01 Feb 2024
Quantum Algorithms for the Pathwise Lasso J. F. Doriguello Debbie Lim Chi Seng Pun Patrick Rebentrost Tushar Vaidya 42 1 0 21 Dec 2023
Regularization properties of adversarially-trained linear regression Antônio H. Ribeiro Dave Zachariah Francis Bach Thomas B. Schon AAML 36 8 0 16 Oct 2023
Post-Selection Inference for Sparse Estimation Joe Suzuki 11 0 0 09 Oct 2023
Robust penalized least squares of depth trimmed residuals regression for high-dimensional data Yijun Zuo 13 1 0 04 Sep 2023
A Unified Framework for Pattern Recovery in Penalized and Thresholded Estimation and its Geometry P. Graczyk U. Schneider T. Skalski P. Tardivel 23 2 0 19 Jul 2023
An extended latent factor framework for ill-posed linear regression G. Finocchio Tatyana Krivobokova 37 2 0 17 Jul 2023
Conformalization of Sparse Generalized Linear Models E. Guha Eugène Ndiaye X. Huo 30 3 0 11 Jul 2023
Optimal Sets and Solution Paths of ReLU Networks Aaron Mishkin Mert Pilanci 42 3 0 31 May 2023
Single-Model Attribution of Generative Models Through Final-Layer Inversion M. Laszkiewicz Jonas Ricker Johannes Lederer Asja Fischer 31 4 0 26 May 2023
Variation Spaces for Multi-Output Neural Networks: Insights on Multi-Task Learning and Network Compression Joseph Shenouda Rahul Parhi Kangwook Lee Robert D. Nowak 33 12 0 25 May 2023
Generalization and Estimation Error Bounds for Model-based Neural Networks Avner Shultzman Eyar Azar M. Rodrigues Yonina C. Eldar 21 7 0 19 Apr 2023
Saddle-to-Saddle Dynamics in Diagonal Linear Networks Scott Pesme Nicolas Flammarion 31 35 0 02 Apr 2023
The Voronoigram: Minimax Estimation of Bounded Variation Functions From Scattered Data Addison J. Hu Alden Green R. Tibshirani 31 4 0 30 Dec 2022
Existence and uniqueness of weighted generalized $ψ$ -estimators M. Barczy Zsolt Páles 21 1 0 11 Nov 2022
Testing Heteroskedasticity in High-Dimensional Linear Regression Akira Shinkyu 21 1 0 31 Oct 2022
Lasso Monte Carlo, a Variation on Multi Fidelity Methods for High Dimensional Uncertainty Quantification Arnau Albà R. Boiger D. Rochman Andreas Adelmann 13 1 0 07 Oct 2022
Generalization In Multi-Objective Machine Learning Peter Súkeník Christoph H. Lampert AI4CE 31 5 0 29 Aug 2022
Small Tuning Parameter Selection for the Debiased Lasso Akira Shinkyu N. Sueishi 13 1 0 18 Aug 2022
An Accelerated Doubly Stochastic Gradient Method with Faster Explicit Model Identification Runxue Bao Bin Gu Heng-Chiao Huang 18 16 0 11 Aug 2022
Provably tuning the ElasticNet across instances Maria-Florina Balcan M. Khodak Dravyansh Sharma Ameet Talwalkar 42 13 0 20 Jul 2022
Automatic differentiation of nonsmooth iterative algorithms Jérôme Bolte Edouard Pauwels Samuel Vaiter 23 22 0 31 May 2022
Surprises in adversarially-trained linear regression Antônio H. Ribeiro Dave Zachariah Thomas B. Schon AAML 110 2 0 25 May 2022
Distributed Dynamic Safe Screening Algorithms for Sparse Regularization Runxue Bao Xidong Wu Wenhan Xian Heng-Chiao Huang 31 1 0 23 Apr 2022
Beyond L1: Faster and Better Sparse Models with skglm Quentin Bertrand Quentin Klopfenstein Pierre-Antoine Bannier Gauthier Gidel Mathurin Massias 22 11 0 16 Apr 2022
Sensitivity of sparse codes to image distortions Kyle L. Luther H. S. Seung 13 2 0 15 Apr 2022
Observable adjustments in single-index models for regularized M-estimators Pierre C. Bellec 38 10 0 14 Apr 2022
Pattern recovery by SLOPE M. Bogdan Xavier Dupuis P. Graczyk Bartosz Kołodziejek T. Skalski P. Tardivel Maciej Wilczyñski 19 7 0 22 Mar 2022
Cluster Stability Selection Gregory Faletto Jacob Bien 34 4 0 03 Jan 2022
Sparsest Univariate Learning Models Under Lipschitz Constraint Shayan Aziznejad Thomas Debarre M. Unser 21 4 0 27 Dec 2021
Variable Selection and Regularization via Arbitrary Rectangle-range Generalized Elastic Net Yujia Ding Qidi Peng Zhengming Song Hansen Chen 48 6 0 14 Dec 2021
Efficient and robust high-dimensional sparse logistic regression via nonlinear primal-dual hybrid gradient algorithms Jérome Darbon G. P. Langlois 16 1 0 30 Nov 2021
Characterization of Frequent Online Shoppers using Statistical Learning with Sparsity R. Sambasivan M. Burgess Jörg Schad Arthur K. Keen Christopher Woodward Alexander Geenen Sachin Sharma 13 1 0 11 Nov 2021
Robust lEarned Shrinkage-Thresholding (REST): Robust unrolling for sparse recover Wei Pu Chao Zhou Yonina C. Eldar M. Rodrigues OOD 15 1 0 20 Oct 2021
Assessing the Lockdown Effects on Air Quality during COVID-19 Era Ioannis Kavouras Eftychios E. Protopapadakis Maria Kaselimi Emmanuel Sardis N. Doulamis 6 0 0 25 Jun 2021
Understanding approximate and unrolled dictionary learning for pattern recovery Benoit Malézieux Thomas Moreau M. Kowalski MU 22 10 0 11 Jun 2021
On the Use of Minimum Penalties in Statistical Learning Ben Sherwood Bradley S. Price 17 2 0 09 Jun 2021
Nonsmooth Implicit Differentiation for Machine Learning and Optimization Jérôme Bolte Tam Le Edouard Pauwels Antonio Silveti-Falls 24 54 0 08 Jun 2021
Learning Gaussian Mixtures with Generalised Linear Models: Precise Asymptotics in High-dimensions Bruno Loureiro G. Sicuro Cédric Gerbelot Alessandro Pacco Florent Krzakala Lenka Zdeborová 16 58 0 07 Jun 2021
Stable and Interpretable Unrolled Dictionary Learning Bahareh Tolooshams Demba E. Ba 13 13 0 31 May 2021
Efficient and Modular Implicit Differentiation Mathieu Blondel Quentin Berthet Marco Cuturi Roy Frostig Stephan Hoyer Felipe Llinares-López Fabian Pedregosa Jean-Philippe Vert 27 217 0 31 May 2021