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Dimension-free PAC-Bayesian bounds for matrices, vectors, and linear least squares regression

7 December 2017

Papers citing "Dimension-free PAC-Bayesian bounds for matrices, vectors, and linear least squares regression"

28 / 28 papers shown

Title
Time-Uniform Confidence Spheres for Means of Random Vectors Ben Chugg Hongjian Wang Aaditya Ramdas 203 5 0 14 Nov 2023
Covariance Estimation under Missing Observations and $L_4-L_2$ Moment Equivalence Pedro Abdalla 67 1 0 22 May 2023
Dimension-free Bounds for Sum of Dependent Matrices and Operators with Heavy-Tailed Distribution Shogo H. Nakakita Pierre Alquier Masaaki Imaizumi 88 2 0 18 Oct 2022
Covariance Estimation: Optimal Dimension-free Guarantees for Adversarial Corruption and Heavy Tails Pedro Abdalla Nikita Zhivotovskiy 84 25 0 17 May 2022
Catoni-style confidence sequences for heavy-tailed mean estimation Hongjian Wang Aaditya Ramdas 126 32 0 02 Feb 2022
Dimension-free Bounds for Sums of Independent Matrices and Simple Tensors via the Variational Principle Nikita Zhivotovskiy 79 35 0 18 Aug 2021
High Dimensional Differentially Private Stochastic Optimization with Heavy-tailed Data Lijie Hu Shuo Ni Hanshen Xiao Di Wang 148 53 0 23 Jul 2021
Robust learning with anytime-guaranteed feedback Matthew J. Holland OOD 26 0 0 24 May 2021
Concentration study of M-estimators using the influence function Timothée Mathieu 75 8 0 09 Apr 2021
Distribution-Free Robust Linear Regression Jaouad Mourtada Tomas Vaskevicius Nikita Zhivotovskiy OOD 74 24 0 25 Feb 2021
New bounds for $k$ -means and information $k$ -means Gautier Appert O. Catoni 69 5 0 14 Jan 2021
Optimal Mean Estimation without a Variance Yeshwanth Cherapanamjeri Nilesh Tripuraneni Peter L. Bartlett Michael I. Jordan 77 23 0 24 Nov 2020
Differentially Private (Gradient) Expectation Maximization Algorithm with Statistical Guarantees Di Wang Jiahao Ding Lijie Hu Zejun Xie Miao Pan Jinhui Xu 33 0 0 22 Oct 2020
On Differentially Private Stochastic Convex Optimization with Heavy-tailed Data Di Wang Hanshen Xiao S. Devadas Jinhui Xu 81 57 0 21 Oct 2020
PAC-Bayes unleashed: generalisation bounds with unbounded losses Maxime Haddouche Benjamin Guedj Omar Rivasplata John Shawe-Taylor 100 56 0 12 Jun 2020
Universal Robust Regression via Maximum Mean Discrepancy Pierre Alquier Mathieu Gerber 139 16 0 01 Jun 2020
Generalized Resilience and Robust Statistics Banghua Zhu Jiantao Jiao Jacob Steinhardt 96 45 0 19 Sep 2019
Lecture Notes: Selected topics on robust statistical learning theory M. Lerasle OOD 75 32 0 28 Aug 2019
A Unified Approach to Robust Mean Estimation Adarsh Prasad Sivaraman Balakrishnan Pradeep Ravikumar 63 27 0 01 Jul 2019
Distribution-robust mean estimation via smoothed random perturbations Matthew J. Holland OOD 68 5 0 25 Jun 2019
Mean estimation and regression under heavy-tailed distributions--a survey Gabor Lugosi S. Mendelson 105 246 0 10 Jun 2019
Robust subgaussian estimation of a mean vector in nearly linear time Jules Depersin Guillaume Lecué 143 92 0 07 Jun 2019
PAC-Bayes under potentially heavy tails Matthew J. Holland 128 42 0 20 May 2019
Robust Inference via Multiplier Bootstrap Xi Chen Wen-Xin Zhou 54 32 0 18 Mar 2019
Fast Mean Estimation with Sub-Gaussian Rates Yeshwanth Cherapanamjeri Nicolas Flammarion Peter L. Bartlett 84 78 0 06 Feb 2019
Robust descent using smoothed multiplicative noise Matthew J. Holland OOD 79 27 0 15 Oct 2018
Near-optimal mean estimators with respect to general norms Gábor Lugosi S. Mendelson 61 40 0 16 Jun 2018
MONK -- Outlier-Robust Mean Embedding Estimation by Median-of-Means M. Lerasle Z. Szabó Gaspar Massiot Guillaume Lecué 217 36 0 13 Feb 2018