4 citations · 4 across the 5 of their papers we have counts for
5 papers
A Bias-Correction Decentralized Stochastic Gradient Algorithm with Momentum Acceleration
Yuchen Hu, Xi Chen, Weidong Liu +1
Distributed stochastic optimization algorithms can simultaneously process large-scale datasets, significantly accelerating model training. However, their effectiveness is often hin…
Efficient Sparse Least Absolute Deviation Regression with Differential Privacy
Weidong Liu, Xiaojun Mao, Xiaofei Zhang +1
In recent years, privacy-preserving machine learning algorithms have attracted increasing attention because of their important applications in many scientific fields. However, in t…
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…