Regularization and the small-ball method I: sparse recovery

21 January 2016

Papers citing "Regularization and the small-ball method I: sparse recovery"

28 / 28 papers shown

Title
Unleashing the Power of Data Tsunami: A Comprehensive Survey on Data Assessment and Selection for Instruction Tuning of Language Models Yulei Qin Yuncheng Yang Pengcheng Guo Gang Li Hang Shao Yuchen Shi Zihan Xu Yun Gu Ke Li Xing Sun ALM 99 12 0 31 Dec 2024
Statistical learning by sparse deep neural networks Felix Abramovich BDL 39 1 0 15 Nov 2023
Statistical Learning Theory for Control: A Finite Sample Perspective Anastasios Tsiamis Ingvar M. Ziemann Nikolai Matni George J. Pappas 33 73 0 12 Sep 2022
Outlier Robust and Sparse Estimation of Linear Regression Coefficients Takeyuki Sasai Hironori Fujisawa 35 4 0 24 Aug 2022
Robust Methods for High-Dimensional Linear Learning Ibrahim Merad Stéphane Gaïffas OOD 55 3 0 10 Aug 2022
Generalization Error Bounds for Multiclass Sparse Linear Classifiers Tomer Levy F. Abramovich 32 5 0 13 Apr 2022
Safe rules for the identification of zeros in the solutions of the SLOPE problem Clément Elvira Cédric Herzet 35 9 0 22 Oct 2021
On Empirical Risk Minimization with Dependent and Heavy-Tailed Data Abhishek Roy Krishnakumar Balasubramanian Murat A. Erdogdu 49 18 0 06 Sep 2021
On Monte-Carlo methods in convex stochastic optimization Daniel Bartl S. Mendelson 30 8 0 19 Jan 2021
A spectral algorithm for robust regression with subgaussian rates Jules Depersin 23 14 0 12 Jul 2020
Robust subgaussian estimation with VC-dimension Jules Depersin 27 12 0 24 Apr 2020
Multiclass classification by sparse multinomial logistic regression F. Abramovich V. Grinshtein Tomer Levy 21 23 0 04 Mar 2020
De-biasing convex regularized estimators and interval estimation in linear models Pierre C. Bellec Cun-Hui Zhang 39 20 0 26 Dec 2019
Does SLOPE outperform bridge regression? Shuaiwen Wang Haolei Weng A. Maleki 24 19 0 20 Sep 2019
Robust high dimensional learning for Lipschitz and convex losses Geoffrey Chinot Guillaume Lecué M. Lerasle 29 18 0 10 May 2019
Structured Recovery with Heavy-tailed Measurements: A Thresholding Procedure and Optimal Rates Xiaohan Wei 20 11 0 16 Apr 2018
Robust 1-Bit Compressed Sensing via Hinge Loss Minimization Martin Genzel A. Stollenwerk 21 5 0 13 Apr 2018
Convergence rates of least squares regression estimators with heavy-tailed errors Q. Han J. Wellner 21 45 0 07 Jun 2017
Improved bounds for Square-Root Lasso and Square-Root Slope A. Derumigny 33 26 0 08 Mar 2017
Estimation bounds and sharp oracle inequalities of regularized procedures with Lipschitz loss functions Pierre Alquier V. Cottet Guillaume Lecué 42 58 0 05 Feb 2017
Towards the study of least squares estimators with convex penalty Pierre C. Bellec Guillaume Lecué Alexandre B. Tsybakov 30 11 0 31 Jan 2017
Learning from MOM's principles: Le Cam's approach Lecué Guillaume Lerasle Matthieu 40 51 0 08 Jan 2017
Simpler PAC-Bayesian Bounds for Hostile Data Pierre Alquier Benjamin Guedj 89 72 0 23 Oct 2016
On optimality of empirical risk minimization in linear aggregation Adrien Saumard 32 20 0 11 May 2016
SLOPE is Adaptive to Unknown Sparsity and Asymptotically Minimax Weijie Su Emmanuel Candes 65 145 0 29 Mar 2015
Learning without Concentration for General Loss Functions S. Mendelson 63 65 0 13 Oct 2014
Learning without Concentration S. Mendelson 92 333 0 01 Jan 2014
High-dimensional generalized linear models and the lasso Sara van de Geer 201 749 0 04 Apr 2008