55 citations · 58 across the 6 of their papers we have counts for
9 papers · 1 filter
Subsampling and Jackknifing: A Practically Convenient Solution for Large Data Analysis with Limited Computational Resources
Shuyuan Wu, Xuening Zhu, Hansheng Wang
Modern statistical analysis often encounters datasets with large sizes. For these datasets, conventional estimation methods can hardly be used immediately because practitioners oft…
An Asymptotic Analysis of Minibatch-Based Momentum Methods for Linear Regression Models
Yuan Gao, Xuening Zhu, Haobo Qi +3
Momentum methods have been shown to accelerate the convergence of the standard gradient descent algorithm in practice and theory. In particular, the minibatch-based gradient descen…
A Sequential Addressing Subsampling Method for Massive Data Analysis under Memory Constraint
Rui Pan, Yingqiu Zhu, Baishan Guo +2
The emergence of massive data in recent years brings challenges to automatic statistical inference. This is particularly true if the data are too numerous to be read into memory as…
On the Subbagging Estimation for Massive Data
Tao Zou, Xian Li, Xuan Liang +1
This article introduces subbagging (subsample aggregating) estimation approaches for big data analysis with memory constraints of computers. Specifically, for the whole dataset wit…
Estimating Extreme Value Index by Subsampling for Massive Datasets with Heavy-Tailed Distributions
Yongxin Li, Liujun Chen, Deyuan Li +1
Modern statistical analyses often encounter datasets with massive sizes and heavy-tailed distributions. For datasets with massive sizes, traditional estimation methods can hardly b…
Hyperparameter Selection for Subsampling Bootstraps
Yingying Ma, Hansheng Wang
Massive data analysis becomes increasingly prevalent, subsampling methods like BLB (Bag of Little Bootstraps) serves as powerful tools for assessing the quality of estimators for m…