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04/25/2023
A New Inexact Proximal Linear Algorithm with Adaptive Stopping Criteria for Robust Phase Retrieval
This paper considers the robust phase retrieval problem, which can be ca...
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02/13/2023
A Graphical Point Process Framework for Understanding Removal Effects in Multi-Touch Attribution
Marketers employ various online advertising channels to reach customers,...
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12/29/2022
Theoretical Guarantees for Sparse Principal Component Analysis based on the Elastic Net
Sparse principal component analysis (SPCA) is widely used for dimensiona...
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09/30/2021
Power-enhanced simultaneous test of high-dimensional mean vectors and covariance matrices with application to gene-set testing
Power-enhanced tests with high-dimensional data have received growing at...
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09/30/2021
Robust High-Dimensional Regression with Coefficient Thresholding and its Application to Imaging Data Analysis
It is of importance to develop statistical techniques to analyze high-di...
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01/28/2021
Improving Neural Network Robustness through Neighborhood Preserving Layers
Robustness against adversarial attack in neural networks is an important...
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07/18/2020
A Manifold Proximal Linear Method for Sparse Spectral Clustering with Application to Single-Cell RNA Sequencing Data Analysis
Spectral clustering is one of the fundamental unsupervised learning meth...
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05/31/2020
Fisher's combined probability test for high-dimensional covariance matrices
Testing large covariance matrices is of fundamental importance in statis...
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05/03/2020
Riemannian Stochastic Proximal Gradient Methods for Nonsmooth Optimization over the Stiefel Manifold
Riemannian optimization has drawn a lot of attention due to its wide app...
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05/31/2019
Diagonally-Dominant Principal Component Analysis
We consider the problem of decomposing a large covariance matrix into th...
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03/27/2019
An Alternating Manifold Proximal Gradient Method for Sparse PCA and Sparse CCA
Sparse principal component analysis (PCA) and sparse canonical correlati...
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12/21/2017
Model-Based Clustering of Nonparametric Weighted Networks
Water pollution is a major global environmental problem, and it poses a ...
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12/20/2017
Model-Based Clustering of Time-Evolving Networks through Temporal Exponential-Family Random Graph Models
Dynamic networks are a general language for describing time-evolving com...
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11/13/2017
A Review of Dynamic Network Models with Latent Variables
We present a selective review on statistical modeling of dynamic network...
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05/01/2017
Inverse Moment Methods for Sufficient Forecasting using High-Dimensional Predictors
We consider forecasting a single time series using high-dimensional pred...
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12/31/2015
Nonparametric mixture of Gaussian graphical models
Graphical model has been widely used to investigate the complex dependen...
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12/30/2015
Joint limiting laws for high-dimensional independence tests
Testing independence is of significant interest in many important areas ...
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05/27/2015
Sufficient Forecasting Using Factor Models
We consider forecasting a single time series when there is a large numbe...
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10/22/2012