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07/26/2023
Empirical likelihood test for community structure in networks
Network data, characterized by interconnected nodes and edges, is pervas...
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05/25/2023
Matrix Autoregressive Model with Vector Time Series Covariates for Spatio-Temporal Data
In this paper, we propose a new model for forecasting time series data d...
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03/04/2023
Minimax optimal high-dimensional classification using deep neural networks
High-dimensional classification is a fundamentally important research pr...
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02/24/2023
Statistical Inference with Stochastic Gradient Methods under φ-mixing Data
Stochastic gradient descent (SGD) is a scalable and memory-efficient opt...
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02/05/2023
Scalable inference in functional linear regression with streaming data
Traditional static functional data analysis is facing new challenges due...
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09/28/2022
Solar Flare Index Prediction Using SDO/HMI Vector Magnetic Data Products with Statistical and Machine Learning Methods
Solar flares, especially the M- and X-class flares, are often associated...
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07/04/2022
Minimax Optimal Deep Neural Network Classifiers Under Smooth Decision Boundary
Deep learning has gained huge empirical successes in large-scale classif...
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05/17/2022
Deep Neural Network Classifier for Multi-dimensional Functional Data
We propose a new approach, called as functional deep neural network (FDN...
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04/19/2022
Information-theoretic Limits for Testing Community Structures in Weighted Networks
Community detection refers to the problem of clustering the nodes of a n...
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02/23/2022
Statistical Inference for Functional Linear Quantile Regression
We propose inferential tools for functional linear quantile regression w...
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02/11/2022
Statistical Limits for Testing Correlation of Hypergraphs
In this paper, we consider the hypothesis testing of correlation between...
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11/15/2021
An Approach of Bayesian Variable Selection for Ultrahigh Dimensional Multivariate Regression
In many practices, scientists are particularly interested in detecting w...
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06/07/2021
Calibrating multi-dimensional complex ODE from noisy data via deep neural networks
Ordinary differential equations (ODEs) are widely used to model complex ...
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05/21/2021
Online Statistical Inference for Parameters Estimation with Linear-Equality Constraints
Stochastic gradient descent (SGD) and projected stochastic gradient desc...
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05/20/2021
Distributed Adaptive Nearest Neighbor Classifier: Algorithm and Theory
When data is of an extraordinarily large size or physically stored in di...
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05/05/2021
Information Limits for Detecting a Subhypergraph
We consider the problem of recovering a subhypergraph based on an observ...
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04/08/2021
Heterogeneous Dense Subhypergraph Detection
We study the problem of testing the existence of a heterogeneous dense s...
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02/28/2021
Optimal Imperfect Classification for Gaussian Functional Data
Existing works on functional data classification focus on the constructi...
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01/12/2021
Sharp detection boundaries on testing dense subhypergraph
We study the problem of testing the existence of a dense subhypergraph. ...
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12/08/2020
Estimation of the Mean Function of Functional Data via Deep Neural Networks
In this work, we propose a deep neural network method to perform nonpara...
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11/09/2020
A Computationally Efficient Classification Algorithm in Posterior Drift Model: Phase Transition and Minimax Adaptivity
In massive data analysis, training and testing data often come from very...
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04/30/2020
On Deep Instrumental Variables Estimate
The endogeneity issue is fundamentally important as many empirical appli...
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01/19/2020
Optimal Rate of Convergence for Deep Neural Network Classifiers under the Teacher-Student Setting
Classifiers built with neural networks handle large-scale high-dimension...
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11/20/2019
Statistical Inference on Partially Linear Panel Model under Unobserved Linearity
A new statistical procedure, based on a modified spline basis, is propos...
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11/06/2019
Minimax Nonparametric Two-sample Test
We consider the problem of comparing probability densities between two g...
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02/05/2019
Optimal Nonparametric Inference via Deep Neural Network
Deep neural network is a state-of-art method in modern science and techn...
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01/24/2019
Optimal Nonparametric Inference under Quantization
Statistical inference based on lossy or incomplete samples is of fundame...
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10/10/2018
Testing Community Structures for Hypergraphs
Many complex networks in real world can be formulated as hypergraphs whe...
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07/12/2018
A likelihood-ratio type test for stochastic block models with bounded degrees
A fundamental problem in network data analysis is to test Erdös-Rényi mo...
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05/25/2018
How Many Machines Can We Use in Parallel Computing for Kernel Ridge Regression?
This paper attempts to solve a basic problem in distributed statistical ...
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02/17/2018
Nonparametric Testing under Random Projection
A common challenge in nonparametric inference is its high computational ...
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12/30/2012