Graphical Assistant Grouped Network Autoregression Model : A Bayesian Nonpara…
Vector autoregression model is ubiquitous in classical time series data analysis. With the rapid advance of social network sites, time series data over latent graph is becoming increasingly popular…
Learning Human Activity Patterns Using Clustered Point Processes With Active …
Modeling event patterns is a central task in a wide range of disciplines. In applications such as studying human activity patterns, events often arrive clustered with sporadic and long periods of i…
Least-Square Approximation for a Distributed System
In this work, we develop a distributed least-square approximation (DLSA) method that is able to solve a large family of regression problems (e.g., linear regression, logistic regression, and Cox’…
Feature Screening for Massive Data Analysis by Subsampling
Modern statistical analysis often encounters massive datasets with ultrahigh-dimensional features. In this work, we develop a subsampling approach for feature screening with massive datasets. The a…
An Asymptotic Analysis of Random Partition Based Minibatch Momentum Methods f…
Momentum methods have been shown to accelerate the convergence of the standard gradient descent algorithm in practice and theory. In particular, the random partition based minibatch gradient descen…
Network Functional Varying Coefficient Model
We consider functional responses with network dependence observed for each individual at irregular time points. To model both the interindividual dependence and within-individual dynamic correlatio…
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