On Empirical Risk Minimization with Dependent and Heavy-Tailed Data

6 September 2021

Papers citing "On Empirical Risk Minimization with Dependent and Heavy-Tailed Data"

16 / 16 papers shown

Title
Uncertainty-based Offline Variational Bayesian Reinforcement Learning for Robustness under Diverse Data Corruptions Rui Yang Jie Wang Guoping Wu Yangqiu Song AAML OffRL 48 1 0 01 Nov 2024
Robust Max Statistics for High-Dimensional Inference Mingshuo Liu Miles E. Lopes 27 1 0 25 Sep 2024
Data Quality in Edge Machine Learning: A State-of-the-Art Survey M. D. Belgoumri Mohamed Reda Bouadjenek Sunil Aryal Hakim Hacid 47 1 0 01 Jun 2024
Rate-Optimal Non-Asymptotics for the Quadratic Prediction Error Method Charis J. Stamouli Ingvar M. Ziemann George J. Pappas 23 0 0 11 Apr 2024
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
Neural Network Approximation for Pessimistic Offline Reinforcement Learning Di Wu Yuling Jiao Li Shen Haizhao Yang Xiliang Lu OffRL 29 1 0 19 Dec 2023
PAC-Bayes Generalisation Bounds for Dynamical Systems Including Stable RNNs Deividas Eringis J. Leth Zheng-Hua Tan Rafal Wisniewski Mihaly Petreczky 25 3 0 15 Dec 2023
Towards Robust Offline Reinforcement Learning under Diverse Data Corruption Rui Yang Han Zhong Jiawei Xu Amy Zhang Chong Zhang Lei Han Tong Zhang OffRL OnRL 41 15 0 19 Oct 2023
High-dimensional robust regression under heavy-tailed data: Asymptotics and Universality Sining Chen Leonardo Defilippis Bruno Loureiro G. Sicuro 18 10 0 28 Sep 2023
Empirical Risk Minimization for Losses without Variance Guanhua Fang P. Li G. Samorodnitsky 31 1 0 07 Sep 2023
The noise level in linear regression with dependent data Ingvar M. Ziemann Stephen Tu George J. Pappas Nikolai Matni 35 5 0 18 May 2023
Constrained Stochastic Nonconvex Optimization with State-dependent Markov Data Abhishek Roy Krishnakumar Balasubramanian Saeed Ghadimi 14 9 0 22 Jun 2022
Learning with little mixing Ingvar M. Ziemann Stephen Tu 27 27 0 16 Jun 2022
On Monte-Carlo methods in convex stochastic optimization Daniel Bartl S. Mendelson 25 8 0 19 Jan 2021
Learning without Concentration for General Loss Functions S. Mendelson 63 65 0 13 Oct 2014
Learning without Concentration S. Mendelson 90 333 0 01 Jan 2014