55 citations · 109 across the 5 of their papers we have counts for
5 papers
A Selective Review on Statistical Methods for Massive Data Computation: Distributed Computing, Subsampling, and Minibatch Techniques
Xuetong Li, Yuan Gao, Hong Chang +11
This paper presents a selective review of statistical computation methods for massive data analysis. A huge amount of statistical methods for massive data computation have been rap…
EControl: Fast Distributed Optimization with Compression and Error Control
Yuan Gao, Rustem Islamov, Sebastian Stich
Modern distributed training relies heavily on communication compression to reduce the communication overhead. In this work, we study algorithms employing a popular class of contrac…
On the asymptotic properties of a bagging estimator with a massive dataset
Yuan Gao, Riquan Zhang, Hansheng Wang
Bagging is a useful method for large-scale statistical analysis, especially when the computing resources are very limited. We study here the asymptotic properties of bagging estima…
A review of distributed statistical inference
Yuan Gao, Weidong Liu, Hansheng Wang +3
The rapid emergence of massive datasets in various fields poses a serious challenge to traditional statistical methods. Meanwhile, it provides opportunities for researchers to deve…
An Improved Analysis of Stochastic Gradient Descent with Momentum
Yanli Liu, Yuan Gao, Wotao Yin
SGD with momentum (SGDM) has been widely applied in many machine learning tasks, and it is often applied with dynamic stepsizes and momentum weights tuned in a stagewise manner. De…