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08/22/2023
Large-scale Multi-layer Academic Networks Derived from Statistical Publications
The utilization of multi-layer network structures now enables the explan...
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06/07/2023
Quasi-Newton Updating for Large-Scale Distributed Learning
Distributed computing is critically important for modern statistical ana...
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06/07/2023
Subnetwork Estimation for Spatial Autoregressive Models in Large-scale Networks
Large-scale networks are commonly encountered in practice (e.g., Faceboo...
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04/13/2023
Statistical Analysis of Fixed Mini-Batch Gradient Descent Estimator
We study here a fixed mini-batch gradient decent (FMGD) algorithm to sol...
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04/13/2023
Improved Naive Bayes with Mislabeled Data
Labeling mistakes are frequently encountered in real-world applications....
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04/13/2023
On the asymptotic properties of a bagging estimator with a massive dataset
Bagging is a useful method for large-scale statistical analysis, especia...
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04/13/2023
A review of distributed statistical inference
The rapid emergence of massive datasets in various fields poses a seriou...
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04/13/2023
Subsampling and Jackknifing: A Practically Convenient Solution for Large Data Analysis with Limited Computational Resources
Modern statistical analysis often encounters datasets with large sizes. ...
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04/12/2023
Testing Sufficiency for Transfer Learning
Modern statistical analysis often encounters high dimensional models but...
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04/05/2023
Distributed Logistic Regression for Massive Data with Rare Events
Large-scale rare events data are commonly encountered in practice. To ta...
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02/15/2023
Optimal Subsampling Bootstrap for Massive Data
The bootstrap is a widely used procedure for statistical inference becau...
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11/23/2022
Embedding Compression for Text Classification Using Dictionary Screening
In this paper, we propose a dictionary screening method for embedding co...
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05/06/2022
Network Gradient Descent Algorithm for Decentralized Federated Learning
We study a fully decentralized federated learning algorithm, which is a ...
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11/02/2021
An Asymptotic Analysis of Minibatch-Based Momentum Methods for Linear Regression Models
Momentum methods have been shown to accelerate the convergence of the st...
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10/03/2021
A Sequential Addressing Subsampling Method for Massive Data Analysis under Memory Constraint
The emergence of massive data in recent years brings challenges to autom...
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02/28/2021
On the Subbagging Estimation for Massive Data
This article introduces subbagging (subsample aggregating) estimation ap...
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07/04/2020
Estimating Extreme Value Index by Subsampling for Massive Datasets with Heavy-Tailed Distributions
Modern statistical analyses often encounter datasets with massive sizes ...
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06/02/2020
Hyperparameter Selection for Subsampling Bootstraps
Massive data analysis becomes increasingly prevalent, subsampling method...
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04/07/2020
Automatic, Dynamic, and Nearly Optimal Learning Rate Specification by Local Quadratic Approximation
In deep learning tasks, the learning rate determines the update step siz...
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04/06/2020
Efficient Estimation for Generalized Linear Models on a Distributed System with Nonrandomly Distributed Data
Distributed systems have been widely used in practice to accomplish data...
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08/14/2019
Least Squares Approximation for a Distributed System
In this work we develop a distributed least squares approximation (DLSA)...
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03/05/2018
