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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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04/14/2023
Subsampling-Based Modified Bayesian Information Criterion for Large-Scale Stochastic Block Models
Identifying the number of communities is a fundamental problem in commun...
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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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03/05/2022
Wasserstein Distance-based Spectral Clustering with Application to Transaction Data
With the rapid development of online payment platforms, it is now possib...
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10/19/2021
Subsampling Spectral Clustering for Large-Scale Social Networks
Online social network platforms such as Twitter and Sina Weibo have been...
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04/30/2021
Vehicle Re-identification Method Based on Vehicle Attribute and Mutual Exclusion Between Cameras
Vehicle Re-identification aims to identify a specific vehicle across tim...
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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