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02/12/2023
Bayesian Methods in Tensor Analysis
Tensors, also known as multidimensional arrays, are useful data structur...
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11/21/2022
Precision education: A Bayesian nonparametric approach for handling item and examinee heterogeneity in assessment data
We propose a novel nonparametric Bayesian IRT model in this paper by int...
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05/20/2022
Multidimensional heterogeneity learning for count value tensor data with applications to field goal attempt analysis of NBA players
We propose a multidimensional tensor clustering approach for studying ho...
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05/15/2022
How Much Does Home Field Advantage Matter in Soccer Games? A Causal Inference Approach for English Premier League Analysis
In many sports, it is commonly believed that the home team has an advant...
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03/28/2021
Nonparametric tests for treatment effect heterogeneity in observational studies
We consider the problem of testing for treatment effect heterogeneity in...
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01/07/2021
Addressing patient heterogeneity in disease predictive model development
This paper addresses patient heterogeneity associated with prediction pr...
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12/26/2020
Graph signal denoising using t-shrinkage priors
We study the graph signal denoising problem by estimating a piecewise co...
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12/18/2020
Identifying latent groups in spatial panel data using a Markov random field constrained product partition model
Understanding the heterogeneity over spatial locations is an important p...
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10/16/2020
Analysis of professional basketball field goal attempts via a Bayesian matrix clustering approach
We propose a Bayesian nonparametric matrix clustering approach to analyz...
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08/20/2020
Spatial homogeneity learning for spatially correlated functional data with application to COVID-19 Growth rate curves
We study the spatial heterogeneity effect on regional COVID-19 pandemic ...
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04/11/2020
Covariance Estimation for Matrix-valued Data
Covariance estimation for matrix-valued data has received an increasing ...
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10/24/2019
Finite Mixtures of ERGMs for Ensembles of Networks
Ensembles of networks arise in many scientific fields, but currently the...
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03/31/2019
Nonparametric Matrix Response Regression with Application to Brain Imaging Data Analysis
With the rapid growth of neuroimaging technologies, a great effort has b...
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10/08/2018
Modeling Brain Connectivity with Graphical Models on Frequency Domain
Multichannel electroencephalograms (EEGs) have been widely used to study...
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09/24/2018
Matrix Linear Discriminant Analysis
We propose a novel linear discriminant analysis approach for the classif...
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08/31/2018
Generalized probabilistic principal component analysis of correlated data
Principal component analysis (PCA) is a well-established tool in machine...
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08/06/2018
Regularized matrix data clustering and its application to image analysis
In this paper, we propose a regularized mixture probabilistic model to c...
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12/11/2017
Asymptotically optimal empirical Bayes inference in a piecewise constant sequence model
Inference on high-dimensional parameters in structured linear models is ...
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10/22/2017