Learning subgaussian classes : Upper and minimax bounds

21 May 2013

Papers citing "Learning subgaussian classes : Upper and minimax bounds"

23 / 23 papers shown

Title
Sharp Rates in Dependent Learning Theory: Avoiding Sample Size Deflation for the Square Loss Ingvar M. Ziemann Stephen Tu George J. Pappas Nikolai Matni 54 8 0 08 Feb 2024
A Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized Linear Models Lijia Zhou Frederic Koehler Pragya Sur Danica J. Sutherland Nathan Srebro 88 9 0 21 Oct 2022
Learning with little mixing Ingvar M. Ziemann Stephen Tu 34 27 0 16 Jun 2022
Exponential Tail Local Rademacher Complexity Risk Bounds Without the Bernstein Condition Varun Kanade Patrick Rebeschini Tomas Vaskevicius 39 10 0 23 Feb 2022
Non-Asymptotic Guarantees for Robust Statistical Learning under Infinite Variance Assumption Lihu Xu Fang Yao Qiuran Yao Huiming Zhang 38 10 0 10 Jan 2022
A spectral algorithm for robust regression with subgaussian rates Jules Depersin 23 14 0 12 Jul 2020
Empirical Risk Minimization under Random Censorship: Theory and Practice Guillaume Ausset Stéphan Clémençon François Portier 20 5 0 05 Jun 2019
Robust high dimensional learning for Lipschitz and convex losses Geoffrey Chinot Guillaume Lecué M. Lerasle 29 18 0 10 May 2019
Robust classification via MOM minimization Guillaume Lecué M. Lerasle Timlothée Mathieu 16 47 0 09 Aug 2018
Localized Gaussian width of $M$ -convex hulls with applications to Lasso and convex aggregation Pierre C. Bellec 21 17 0 30 May 2017
Estimation bounds and sharp oracle inequalities of regularized procedures with Lipschitz loss functions Pierre Alquier V. Cottet Guillaume Lecué 40 58 0 05 Feb 2017
Learning from MOM's principles: Le Cam's approach Lecué Guillaume Lerasle Matthieu 38 51 0 08 Jan 2017
Risk minimization by median-of-means tournaments Gabor Lugosi S. Mendelson 16 130 0 02 Aug 2016
On optimality of empirical risk minimization in linear aggregation Adrien Saumard 28 20 0 11 May 2016
High-Dimensional Estimation of Structured Signals from Non-Linear Observations with General Convex Loss Functions Martin Genzel 30 45 0 10 Feb 2016
`local' vs. `global' parameters -- breaking the gaussian complexity barrier S. Mendelson 35 24 0 09 Apr 2015
On aggregation for heavy-tailed classes S. Mendelson 49 28 0 25 Feb 2015
The generalized Lasso with non-linear observations Y. Plan Roman Vershynin 41 195 0 13 Feb 2015
Learning without Concentration for General Loss Functions S. Mendelson 63 65 0 13 Oct 2014
Geometric Inference for General High-Dimensional Linear Inverse Problems T. Tony Cai Tengyuan Liang Alexander Rakhlin 54 27 0 17 Apr 2014
Performance of empirical risk minimization in linear aggregation Guillaume Lecué S. Mendelson FedML 55 40 0 24 Feb 2014
Learning without Concentration S. Mendelson 92 333 0 01 Jan 2014
Concentration in unbounded metric spaces and algorithmic stability A. Kontorovich 35 53 0 04 Sep 2013