12 citations · 12 across the 5 of their papers we have counts for
5 papers
Robust Variational Bayes by Min-Max Median Aggregation
Jiawei Yan, Ju Liu, Weidong Liu +1
We propose a robust and scalable variational Bayes (VB) framework designed to effectively handle contamination and outliers in dataset. Our approach partitions the data into di…
Online Estimation and Inference for Robust Policy Evaluation in Reinforcement Learning
Weidong Liu, Jiyuan Tu, Xi Chen +1
Reinforcement learning has emerged as one of the prominent topics attracting attention in modern statistical learning, with policy evaluation being a key component. Unlike the trad…
Distributed Semi-Supervised Sparse Statistical Inference
Jiyuan Tu, Weidong Liu, Xiaojun Mao +1
The debiased estimator is a crucial tool in statistical inference for high-dimensional model parameters. However, constructing such an estimator involves estimating the high-dimens…
Majority Vote for Distributed Differentially Private Sign Selection
Weidong Liu, Jiyuan Tu, Xiaojun Mao +1
Privacy-preserving data analysis has become more prevalent in recent years. In this study, we propose a distributed group differentially private Majority Vote mechanism, for the si…
Variance Reduced Median-of-Means Estimator for Byzantine-Robust Distributed Inference
Jiyuan Tu, Weidong Liu, Xiaojun Mao +1
This paper develops an efficient distributed inference algorithm, which is robust against a moderate fraction of Byzantine nodes, namely arbitrary and possibly adversarial machines…