Risk minimization by median-of-means tournaments

2 August 2016

Gabor Lugosi

Papers citing "Risk minimization by median-of-means tournaments"

38 / 38 papers shown

Title
Do we really need the Rademacher complexities? Daniel Bartl S. Mendelson 70 0 0 24 Feb 2025
Robust Consensus in Ranking Data Analysis: Definitions, Properties and Computational Issues Morgane Goibert Clément Calauzènes Ekhine Irurozki Stéphan Clémenccon 26 1 0 22 Mar 2023
Robust empirical risk minimization via Newton's method Eirini Ioannou Muni Sreenivas Pydi Po-Ling Loh 23 2 0 30 Jan 2023
On deviation probabilities in non-parametric regression Anna Ben-Hamou A. Guyader 37 1 0 25 Jan 2023
On Medians of (Randomized) Pairwise Means Pierre Laforgue Stéphan Clémençon Patrice Bertail 29 12 0 01 Nov 2022
On Catoni's M-Estimation Pengtao Li Hanchao Wang 19 0 0 15 Oct 2022
Outlier Robust and Sparse Estimation of Linear Regression Coefficients Takeyuki Sasai Hironori Fujisawa 35 4 0 24 Aug 2022
Rank-based Decomposable Losses in Machine Learning: A Survey Shu Hu Xin Wang Siwei Lyu 40 32 0 18 Jul 2022
A universal robustification procedure Riccardo Passeggeri Nancy Reid 18 0 0 14 Jun 2022
Covariance Estimation: Optimal Dimension-free Guarantees for Adversarial Corruption and Heavy Tails Pedro Abdalla Nikita Zhivotovskiy 40 25 0 17 May 2022
Byzantine-Robust Federated Linear Bandits Ali Jadbabaie Haochuan Li Jian Qian Yi Tian FedML 34 12 0 03 Apr 2022
Exponential Tail Local Rademacher Complexity Risk Bounds Without the Bernstein Condition Varun Kanade Patrick Rebeschini Tomas Vaskevicius 41 10 0 23 Feb 2022
Do we need to estimate the variance in robust mean estimation? Qiang Sun OOD 32 7 0 30 Jun 2021
Distribution-Free Robust Linear Regression Jaouad Mourtada Tomas Vaskevicius Nikita Zhivotovskiy OOD 36 23 0 25 Feb 2021
On Monte-Carlo methods in convex stochastic optimization Daniel Bartl S. Mendelson 30 8 0 19 Jan 2021
Optimal Mean Estimation without a Variance Yeshwanth Cherapanamjeri Nilesh Tripuraneni Peter L. Bartlett Michael I. Jordan 26 21 0 24 Nov 2020
A spectral algorithm for robust regression with subgaussian rates Jules Depersin 23 14 0 12 Jul 2020
Robust Compressed Sensing using Generative Models A. Jalal Liu Liu A. Dimakis Constantine Caramanis 21 39 0 16 Jun 2020
Generalization Bounds in the Presence of Outliers: a Median-of-Means Study Pierre Laforgue Guillaume Staerman Stéphan Clémençon 16 3 0 09 Jun 2020
Universal Robust Regression via Maximum Mean Discrepancy Pierre Alquier Mathieu Gerber 40 15 0 01 Jun 2020
TAdam: A Robust Stochastic Gradient Optimizer Wendyam Eric Lionel Ilboudo Taisuke Kobayashi Kenji Sugimoto ODL 22 12 0 29 Feb 2020
All-In-One Robust Estimator of the Gaussian Mean A. Dalalyan A. Minasyan 35 25 0 04 Feb 2020
Robust Aggregation for Federated Learning Krishna Pillutla Sham Kakade Zaïd Harchaoui FedML 42 632 0 31 Dec 2019
Empirical Risk Minimization under Random Censorship: Theory and Practice Guillaume Ausset Stéphan Clémençon François Portier 25 5 0 05 Jun 2019
A Primer on PAC-Bayesian Learning Benjamin Guedj 20 221 0 16 Jan 2019
Uniform bounds for robust mean estimators Stanislav Minsker OOD FedML 10 35 0 09 Dec 2018
Robust classification via MOM minimization Guillaume Lecué M. Lerasle Timlothée Mathieu 16 47 0 09 Aug 2018
Defending Against Saddle Point Attack in Byzantine-Robust Distributed Learning Dong Yin Yudong Chen Kannan Ramchandran Peter L. Bartlett FedML 32 98 0 14 Jun 2018
High Dimensional Robust Sparse Regression L. Liu Yanyao Shen Tianyang Li Constantine Caramanis 14 71 0 29 May 2018
Solvable Integration Problems and Optimal Sample Size Selection R. Kunsch E. Novak Daniel Rudolf 25 15 0 22 May 2018
Robust Estimation via Robust Gradient Estimation Adarsh Prasad A. Suggala Sivaraman Balakrishnan Pradeep Ravikumar 30 220 0 19 Feb 2018
MONK -- Outlier-Robust Mean Embedding Estimation by Median-of-Means M. Lerasle Z. Szabó Gaspar Massiot Guillaume Lecué 36 35 0 13 Feb 2018
Convergence rates of least squares regression estimators with heavy-tailed errors Q. Han J. Wellner 19 45 0 07 Jun 2017
Sub-Gaussian estimators of the mean of a random vector Gábor Lugosi S. Mendelson 22 169 0 01 Feb 2017
Learning from MOM's principles: Le Cam's approach Lecué Guillaume Lerasle Matthieu 38 51 0 08 Jan 2017
Simpler PAC-Bayesian Bounds for Hostile Data Pierre Alquier Benjamin Guedj 89 72 0 23 Oct 2016
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