如何学习学习方法论? ——兼论大模型的本质

Causal inspired and robust statistical machine learning

Convergence and Implicit Regularization of Deep Learning Optimizers

Covariate adjustment in multi-armed, possibly factorial experiments

An instrumental variable method for point processes

Introducing the specificity score: a measure of causality beyond P value

Privacy preserving decentralized learning

Huber Principal Component Analysis for Large-dimensional Factor Models

Score function-based tests for ultrahigh-dimensional linear models

Model-free screening procedure for ultrahigh-dimensional survival data based on Hilbert-Schmidt independence criterion

Mapping the Marginalized Groups with Presence-Only Data

Lagrangian Inference for Ranking Problems

Multiple-Splitting Projection Test for High-Dimensional Mean Vectors

Model-Free Conditional Feature Screening with FDR Control

From sparse to dense functional data in high dimensions: revisiting phase transitions from a non-asymptotic perspective

Statistical Learning and Matching Markets

A New Perspective on Empirical Likelihood-Based Inference for Nonparametric Regression: Robust Bias Correction and Wilks Phenomenon

Combining Mendelian randomization and network deconvolution for inference of causal networks with GWAS summary data

Individualized online policy optimization for functional data

Exponential-Family Principal Component Analysis of Two-Dimensional Functional Data with Serial Correlation

Testing Linearity In Semi-Functional Partially Linear Regression Models

Estimation and inference of change points in locally stationary functional time series

Limiting distributions for eigenvalues of sample correlation matrices from heavy-tailed populations

Asymptotics of the spiked eigenvalues of large signal plus noise matrices

Sampling without replacement from a high dimensional finite population

Clustering high-dimensional data: a mean-covariance-based apOn the asymptotic properties of the centerd and noncentered large dimensional signal-plus-noise models with their applications.proach

Sliced Inverse Regression with large structural dimension

A Unified Generalization of Inverse Regression Via Adaptive Column Selection

Factor augmented inverse regression and its application to microbiome data analysis

神经网络遇见随机森林

Optimal Individualized Treatment Rule For Combination Treatments Under Budget Constraints

Differentially Private Data Release for Mixed-type Data via Latent Factor Models

Adaptive Designs and Precision Medicine

Seamless Phase II/III Clinical Trials with Covariate Adaptive Randomization

Community detection for weighted bipartite networks

Estimation of the number of spiked eigenvalues in a covariance matrix by bulk eigenvalue matching analysis

Separating the Human Touch from AI-Generated Text using Higher Criticism

On PC Adjustments for High Dimensional Association Studies

A probability approximation framework with applications

Cramer's moderate deviations for martingales with applications

Cramér-type Moderate Deviation for Quadratic Forms with a Fast Rate

Cramér-type moderate deviations for local dependent random variables

Deep Nonparametric Estimation: Approximation, Generalization, and Overparameterization

A Sequential Addressing Subsampling Method for Massive Data Analysis under Memory Constraint

Nonasymptotic theory for two-layer neural networks: Beyond the bias-variance trade-off

Grid Point Approximation for Distributed Nonparametric Smoothing and Prediction

An efficient tensor regression for high-dimensional data

Dimension agnostic change point detection

A Two-Way Heterogeneity Model For Dynamic Networks

Factor Modelling for Clustering High-dimensional Time Series

Metric Distribution Function

基于模拟学习方法论SLeM的元学习理论、算法与应用

Deep Over-parameterized Quantile Regression

Differentiable Neural Networks With Repu Activation: With Applications To Score Estimation And Isotonic Regression

A general M-estimation theory in semi-supervised framework

Semiparametric inference for quantile regression in imbalanced semi-supervised distributed system

Renewable Quantile Regression with Heterogeneous Streaming Datasets

Deep Sufficient Representation Learning via Mutual Information". And the abstract is attached below

Are Bond Returns Predictable with Real-Time Macro Data?

Control interactive fixed effects with diversified projections

Estimating Social Network Models with Missing Links

Estimation and Inference for Latent Group Structures with Structural Instabilities

Causal structural learning for improving HIV testing and treatment access

Learning Network Properties without Network Data -- A Correlated Network Scale-up Model

婚姻状况变化率的贝叶斯估计与预测

Tree-Regularized Bayesian Latent Class Analysis for Improving Weakly Separated Dietary Pattern Subtyping in Small-Sized Subpopulations

Individual-centered partial information in social networks

Estimating the Number of Communities with Individual-centered Partial Information

SIMPLE-RC: Group Network Inference with Non-Sharp Nulls and Weak Signals

Spectral gap and edge universality of dense random regular graphs

Flexible Functional Treatment Effect Estimation

Interpoint-Ranking Sign Covariance for Test of Independence

Causal Inference on Distribution Functions

Theory of functional principal components analysis for noisy and discretely observed data

Estimating Heterogeneous Treatment Effect at High Quantiles for Heavy-Tailed Distributions

A Decorrelating and Debiasing Approach to Simultaneous Inference for High-Dimensional Confounded Models

Augmented two-step estimating equations with nuisance functionals and complex survey data

Unified distributed inference for a class of problems with nonsmooth loss

Causal Mediation Analysis with a Three-Dimensional Image Mediator

Robust Covariate Balancing Method in Learning Optimal Individualized Treatment Regimes

An efficient tensor regression for high-dimensional data

Randomization-based joint central limit theorem and efficient covariate adjustment in stratified 2^K factorial experiments

Change-point detection in a high-dimensional multinomial sequence based on mutual information

A Generalized Knockoff Procedure for FDR Control in Structural Change Detection

Computationally efficient and data-adaptive changepoint inference in high dimension

Two-Sample and Change-Point Inference for Non-Euclidean Valued Time Series

基于眼底图像简历糖尿病视网膜病变的诊断与预测模型

Estimating COVID-19 Vaccine Protection Rates via Dynamic Epidemic Models

Trends and characteristics of multiple births, premature births, and stillbirths in Shenzhen: A retrospective study over a decade

Infinite Latent Feature Models for Mixed Malaria Infections

统计大数据治理及智能化应用实践

Efficient Calibration of Numerical Model Outputs

基于人类行为实验的统计交叉科学研究

去粗取精：法庭科学中的微量物证数据统计有效性鉴定

Estimating graphical models for count data with applications to single-cell gene network

Feature screening for clustering analysis with applications to single-cell RNA-seq data

Improving cross-ancestry genetic prediction by leveraging portable genetic effects

精神分裂症基于脑影像的功能网络分析：寻找TMS潜在靶点

由正交表构造的量子纠缠态

Set Selection of the Number of Change-points with Confidence

Change-point estimation via feedforward neural networks with theoretical guarantee

A shape-based multiple segmentation algorithm for change-point detection

Online network change point detection with missing values and temporal dependence

A New Window-Limited CUSUM Procedure for Online Change Detection and its Data-Driven Robust Variant

Practical operation and theoretical basis of difference-in-difference regression in science of science: The comparative trial on the scientific performance of Nobel laureates versus their coauthors

中国养老保障体系平衡机制：制度目标和参量调整

A Stochastic Jump-process Driving Dynamic Model with Application to Traffic Safety

无人驾驶汽车的市场调研

绿色GDP发展战略规划

司法鉴定中的法庭统计学——证据评价方法与鉴定意见表述

Transfer Learning for High-dimensional Quantile Regression via Convolution Smoothing

基于改进的嵌入物理的神经网络的海洋三维变量场反演

深度学习在部分线性分位数回归模型中的应用

Causal representation based on a GAE-embedded autoencoder for robust domain adaptation

Iterative Least Squares Algorithm for Large-dimensional Matrix Factor Model by Random Projection

Necessary and sufficient conditions for the Marcenko-Pastur law for sample correlation matrices

因子分析最小误差模型及其检验与应用

Matrix Kendall's tau in High-dimensions: A Robust Statistic for Matrix Factor Model

Quasi-maximum likelihood estimation of break point in high-dimensional factor models

分段非对称系统的随机共振及其在变转速旋转机械故障诊断中的应用

Early identification of 6- to 8-year-old children at risk of developing myopia：a comparison of machine learning and statistical approaches

The integrated approach of learning Mycobacterium tuberculosis transmission within and outside households via random directed graph models

An embedding based kernel test: Does eyeglance matters prior to lane change?

基于时间尺度指标建立个体生存时间的动态预测模型——应用到原发性胆汁肝硬化疾病进展研究

肾功能对急性小卒中或短暂性脑缺血发作患者中替格瑞洛联合阿司匹林及氯吡格雷联合阿司匹林的疗效及安全性影响

High-frequency Anticipatory Trading and Its Influences: Small Informed Trader vs. Front-runner

Robust Backtests for Expected Shortfall

Breaking the Factor Zootopia: Factor Selection Using Significant Tests of Multi-Task Lasso

Bias-corrected realized covariation in presence of price staleness

Network transitions in the cryptocurrency market: Evidence from military conflict

Pursuing homogeneity and sparsity in simultaneous quantile regression

Distributed quantile regression for longitudinal big data

Bayesian Inference of Sample Selection Using Quantile Selection Model

Online Updating Huber Robust Regression for Big Data Streams

Robust Bilinear Probabilistic PCA using a Matrix Variate t distribution

Error analysis of generative adversarial network

Clustered Federated Learning based on Nonconvex Pairwise Fusion

Extrapolated Random Tree for Regression

Forecasting High Dimensional Long Memory Time Series based on Memory augmented Gated Recurrent Unit

Adversarial Learning of Distributional Reinforcement Learning

Improved Efficiency in Semiparametric Estimation for two-sample comparison in Semi-Supervised Learning Framework

基于CARR-OVMD-GRU模型的原油期货价格波动性预测

Change Point Detection in Beta Process with High Frequency Data

Capital Allocation with Asset Risks: Amortization by Investable Assets

When Do Models Make Money? A Path from Return Predictability to Profitability

Estimating market liquidity from daily data, marrying Micro structure models and machine learning

Group penalized multinomial logit models and stock return direction prediction

When Statistics Meets Computing: A Few Interesting Problems and Challenges

Recent progress on random graph matching problems

Ordinal Deep Learning for Gene-Environment Interaction analysis

Spatio-temporally Smoothed Deep Survival Neural Network

Iterative Connecting Probability Estimation for Networks

Heterogeneous network estimation for single-cell transcriptomic data via neighborhood selection-based deep neural network

Distributed Learning of Conditional Quantiles in the Reproducing Kernel Hilbert Space

Distributed Estimation and Inference for Semi-parametric Binary Response Models

Decentralized Strongly Convex Optimization with Less Local First-Order Oracle Complexity

Distributed Semi-Supervised Sparse Statistical Inference

Mechanism Analysis and Impact Measurement of the Platform Economy's Social Welfare Effect: An Empirical Study based on the Questionnaire Survey of Merchants on MT Take-out Platform

On the Modelling and Prediction of High-dimensional Functional Time Series

High-dimensional Volatility matrix estimation using Generative Adversarial Networks (GAN) assisted Hybrid Monte Carlo (HMC) for high-frequency data

Multi-modal Knowledge Discovery and Pre-training Cross Vision and Language

Heteroskedastic Sparse PCA in High Dimensions

Regression Analysis of Correlations for Correlated Data

Some Recent Developments in Expected Shortfall Regression

Statistical inferences for complex dependence of multimodal imaging data

Data Integration by Combing Non-probability Data and Big Observational Data for Finite Population Inference

Indirect Sampling Design and Estimation Method Based On Dual Sampling Frame

Non-Probability Samples Fusion Inference Based On Bayesian Framework

Investigating an Alternative for Estimation from a Nonprobability Sample: Matching plus Calibration

How Can Robot Investment Assistant Help: Collecting Information or Providing Advice? Evidence from China

Disclosing and Cooling-Off: An Analysis of Insider Trading Rules

A Two Time-Scale Evolutionary Game Theoretic Approach to Multi-Agent Learning

Spectral Volume Models: High-Frequency Periodicities in Intraday Trading Activities

Damped Anderson Mixing for Deep Reinforcement Learning: Acceleration, Convergence, and Stabilization

Uncovering the Law of Data Separation in Deep Learning

Recurrent Neural Networks with Mixed Hierarchical Structures and EM Algorithm for Natural Language Processing

Community Detection of Discrete-time Temporal Networks under Dynamic Stochastic Block Models

Shrinkage Estimation for Large-dimensional Factor Model with an Observed Variable Network

Estimating cell-type-specific gene co-expression networks from bulk gene expression data

Matrix-valued Network Autoregression Model with Latent Group Structure

Simple measures of uncertainty for model selection

Learning invariant representations for algorithmic fairness and domain generalization with minimax optimality

Eigencurve: Optimal Learning Rate Schedule for SGD on Quadratic Objectives with Skewed Hessian Spectrums

Statistical Inference for Decentralized Federated Learning

Bayesian Quantile Regression with Big Data and Chang-Point Detection

Multistate modeling and structure selection for multi type recurrent events and terminal event

Modelling biomarker variability in joint analysis of longitudinal and time-to-event data

Horseshoe prior for joint-mean covariance model in sparse high dimensional data

Estimation and Inference with Summary Statistics and its Genetic Applications

Are Decision Trees as Powerful as Neural Networks?

Learning Matchings, Maps, and Trajectories

Robust Inference for Federated Meta-Learning

Supervised Topic Modeling: Optimal Estimation and Statistical Inference 

Estimation and Inference in High-Dimensional Generalized Linear Models with Knowledge Transfer

Theoretical Guarantees for Sparse Principal Component Analysis based on the Linear Manifold Approximation

Adaptive False Discovery Rate Control with Privacy Guarantee

Slow Kill for Big Data Learning

New Regression Model: Modal Regression

Tensor Learning in 2020s: Methodology, Theory, and Biomedical Applications

Large-Scale Analytical Platforms for Detecting Splicing-Associated Variants

Feature Selection and Classification over the network with Missing Node Observations with Application in Cancer

Bayesian inference of Tumor Clonal Phylogeny from Single-cell DNA sequencing data

Data integration in Spatial Transcriptomics

A network approach to compute hypervolume under ROC manifold for multi-class biomarkers

Poisson Hurdle Model-based Clustering for Microbiome Data

Integrative analysis of 16S marker-gene and shotgun metagenomic sequencing data improves efficiency of testing microbiome hypotheses

Identification of Prognostic and Predictive Subgroups for Clustered Survival Data

Optimal Clustering by Lloyd Algorithm for Low-Rank Mixture Model

Rising Ownership Network in China

Network Regression and Supervised Centrality Estimation

A Joint Estimation Approach to Sparse Additive Ordinary Differential Equations

Regularized Multi-output Gaussian Convolution Process with Domain Adaptation

Thompson Sampling based Partially Observable Online Change Detection for Exponential Families

Harnessing Industrial Analytics and Intelligence for Digital Transformation

Lattice-based designs possessing quasi-optimal separation distance on all projections

Test-Then-Pool: A uniformly valid inferential framework for data integration

Inference of Heterogeneous Treatment Effects Using Observational Data with High-Dimensional Covariates

ELSA: Efficient Label Shift Adaptation through the Lens of Semiparametric Models

Semiparametric adaptive estimation under informative sampling

Testing strict Stationarity of Complex Time Series

FPLS-DC: Functional partial least squares through distance covariance for imaging genomics

Ball Impurity: Measuring Heterogeneity in General Metric Spaces

On asymptotic normality of a random-localized independence test

数据生产要素核算——关于理论与方法的若干讨论

数据资产、数字经济与经济发展

SNA纳入数据核算的潜在影响与难点解析

数据要素核算问题研究：基本概念及供给使用核算

预测朗格拉普岛核辐射强度的分布

工业数据分析的实践与认识

GeoLake: Bringing Geospatial Support to Lakehouses

AI运动能否让你爱上运动-体育场景下AI应用探索

Temporal label recovery from noisy dynamical data

Deep survival prediction models and applications in cancer researches

A unified quantile framework reveals nonlinear heterogeneous transcriptome-wide associations

STAARpipeline: an all-in-one rare-variant analysis tool for biobank-scale whole-genome sequencing data

Early Identification of Autism Spectrum Disorder by Multi-instrument Fusion: A Clinically Applicable Machine Learning Approach

Quantifying Measures of Treatment Effect on the Between-Group Difference in Competing Risks

Dose change and statistical power in the Aducanumab trial

对外贸易、FDI与中国绿色全要素生产率 ——基于空间计量模型的分析

Distribution-free Contextual Dynamic Pricing

深度学习和多源数据融合的股价预测模型-- 基于Transformer结构

Development and Evaluation of Risk Prediction Models Using Two-Phase Data via Post-stratification

China's Inflation Forecasting with Machine Learning Algorithms

Estimating spot volatility under infinite variation jumps with dependent market microstructure noise

Optimal Execution subject to Reservation Strategies

数字经济对产业结构升级的影响研究

Copula-based multidimensional Markov process

数字经济参与国内大循环的机制和空间特征

Joint triplet sampling enables structure-preserved dimension reduction in single-cell transcriptomic data

Importance Sparsification for Sinkhorn Algorithm with Application in Efficient Echocardiogram Analysis

多基因风险评分与吸烟者大脑加速老化之间的关系

基于个体结构协变网络解决阿尔茨海默病的异质性

High-dimensional Response Growth Curve Modeling for Longitudinal Neuroimaging Analysis

Kernel Copula Density Estimation of Hellinger Correlation

MSAEM Estimation for Multidimensional Four–Parameter Normal Ogive Models

Generalized Two-Mode Latent Space Model

Functional Two-Sample Test based on Projection

Mean regression model for the zero-truncated Poisson distribution and its generalization

A Simple Divide-and-Conquer-based Distributed Method for the Accelerated Time Failure Model

Fitting additive risk models using auxiliary information

Improving marginal hazard ratio estimation using quadratic inference functions

Semiparametric model averaging method for survival probability predictions of patients

Mixture Cure Model with both Semiparametric Components for Interval-Censored Data

Degradation modeling and remaining useful lifetime prediction based on functional variance process

图函数型时间序列的主成分分析（Principal Component Analysis of Graphical-Functional Time Series）

Simultaneous false discovery proportion bounds via knockoffs and closed testing

A novel approach of empirical likelihood with massive data

Multiple-use calibration for infinite many future values and exact simultaneous tolerance intervals in linear regression

Measuring and testing conditional dependence with high-dimensional conditioning variables

Intrinsic minimum average variance estimation for sufficient dimension reduction with symmetric positive difinite matrices and beyond

Robust and Efficient Case-Control Studies with Contaminated Case Pools: A Unified M-Estimation Framework

Matrix-Variate Generalized Linear Model with Measurement Error

最优速率的高维向量自回归模型稳健估计

An Optimal Transport Approach for Selecting a Representative Subsample with Application in Efficient Kernel Density Estimation

A Dynamic Latent Space Model for Bipartite Networks with Nodal Attributes

Varying density coefficient model with density responses

Doubly truncated expectation and variance of univariate generalized skew-elliptical distributions with applications

Inverse Probability Weighting-based Mediation Analysis for Microbiome Data

Statistical and Bioinformatic Analysis of Breast Cancer Methylation Patterns

Gene spatial expression and prognosis prediction by integrated graph and image deep learning model based on HE slides of cancer

Bayesian Inference of Gene Expression Dynamics in Alzheimer Brains

Neural Network on Interval Censored Data with Application to the Prediction of Alzheimer's Disease

Proteome-wide Mendelian Randomization Analysis Identified Potential Drug Targets for Atrial Fibrillation

Community Detection in Temporal Citation Network via a Tensor-based Approach

Kernel regression for estimating regression function and its derivatives with unknown error correlations

A Novel Hypothesis Testing Method of Skew-Normal Distribution Based on the Fourth-order Moment Property

Factor-adjusted model averaging

Consistent Selection of the Number of Groups in Panel Models via Sample-Splitting

Automatic Search Intervals for the Smoothing Parameter in Penalized Splines

Spatial Linear Regression with Covariate Measurement Errors: Inference and Scalable Computation in a Functional Modeling Approach

An efficient PG-INLA algorithm for logistic item response models analysis

分数CIR过程统计行为的数值模拟

High-dimensional Clustering onto Hamiltonian Cycle

Relative error-based distributed estimation in growing dimension

Improving Uncertainty Quantification of Variance Networks by Tree-Structured Learning

High Dimensional Tensor CP Models

Reinforcement Learning via Nonparametric Smoothing in a Continuous-Time Stochastic Setting with Noisy Data

On the multiway PCA

Antipodal Reflection Depth (ARD) and Its Application to Nonparametric Outlier Detection in Multivariate and Functional Data

The Statistical Face of a Region under Monsoon Rainfall in Eastern India

Leveraging Electronic Health Records for Biomedical Research

Cautious explorers generate more future academic impact

On High-Dimensional Gaussian Comparisons For Cross-Validation

Large-scale Multi-layer Academic Networks Derived from Statistical Publications

Introduction to the Database of the ELEMENT Birth Cohorts from the Lens of Biostatistician

The statistical triangle

Co-variance Operator of Banach Valued Random Elements: Viewpoint of U-Statistic

Gaussian Chain Graph Models: Identifiability, Estimation and Asymptotics

Fine-Mapping Causal Variants Using Summary GWAS Statistics with Heritability-induced Dirichlet Decomposition Prior

因之果与果之因

Debiased estimating equation method for summary statistics-based Mendelian randomization

New Tests for High-Dimensional Two-sample Mean Problems with Consideration of Correlation Structure

Statistical inference for counting processes under shape heterogeneity

Selective Conformal Inference with FCR Control

Random fixed boundary flows: a twin sister of principal flow?

Limitations of the Wasserstein MDE

Ensemble Kalman Filter under Fixed and High Dimension 

A Tale of Two Types of Structural Instabilities in High Dimensional Factor Models

Semiparametric copula method for semi-competing risks data subject to interval censoring and left truncation: Application to disability in elderly

深度学习在精准医疗领域中的应用

真实世界研究中倾向评分方法和应用

基于参数g-formula模型的人群干预效应的因果推断研究：以不同降压策略比较为例

Robust Bayesian Regression via Hard Thresholding

非线性期望和强化学习Nonlinear Expectation and Reinforcement Learning

Selection by Prediction: Prediction-Assisted Candidate Screening with Conformal p-values and its Application to Drug Discovery

Integrating Statistical Learning and Deep Learning for More Advanced Material Science

PeerMeta: A Framework of Financial Statement Fraud Detection Based on Peer Effects and Meta Learning

Modeling Medium-sized Cross-sectional Maxima with Autoregressive Conditional GB2 Models

FinRL: A Deep Reinforcement Learning Framework to Automate Trading in Quantitative Finance

Statistical Applications in Stock Investment

Statistical Quantitation of Dynamic PET Scans

Modeling Interactive Biological Pathways From High-Dimensional Gene Expression Trajectories Using Dependent Gaussian Processes

Ensembled Seizure Detection based on Small Training Samples

Knockoff-Based Statistics for the Identification of Putative Causal Genes in Genetic Studies

Controlling the False Discovery Rate in Structural Sparsity: Split Knockoffs

Machine Learning Safety: Enhancing Privacy and Fairness

Significance tests of feature relevance for a black-box learner

Kolmogorov-Smirnov learning by neuron networks with a nonconvex surrogate loss

Fusion of supervised learning and reinforcement learning for dynamic treatment recommendation

基于因果的推荐系统

Correcting for nonignorable nonresponse bias in overestimation of turnout using callabck data

Causal inference for soccer game analysis

Causal inference on distribution functions

Establishing group-level brain structural connectivity incorporating anatomical knowledge under latent space modeling

The promises of multiple outcomes

Bayesian methods for brain-computer interfaces

Efficient calibration of computer models with multivariate output

Effective model averaging for generalized linear models in diverging model spaces

lasso错误快速算法的更正及拓展研究

A Scalable Gaussian Process for Large-Scale Periodic Data

Collapsibility of Conditional Models of CG-Graphical Models

Gaussian mixture reduction with composite transportation divergence

Consistent dynamic Bayesian network learning for an fMRI study of emotion processing

Optimal Excess Risk Bounds via Offset Rademacher Complexity

Model Construction of Quantile Factor Augmented Quantile Autoregression Distributed Lag

Grated Recurrent Unit Network Quantile Regression for Silicon Content Prediction in Blast Furnace

Optimal Sample Splitting for Multiple Outcomes Treatment Effect Detection

Causal inference for semi-competing risks via multi-state models

Treatment Effect Estimation with Censored Outcome and Covariate Selection

An Approximated Collapsed Variational Bayes Approach to Variable Selection in Linear Regression

Dynamic treatment effects: high-dimensional double robust inference under model misspecification

On Adaptive Kernel Learning for Nonparametric Regression and Classification

Optimal One-Pass Nonparametric Estimation Under Memory Constraint

Distributed Estimation and Inference for Spatial Autoregression Model with Large Scale Networks

Transductive Matrix Completion with Calibration for Multi-Task Learning

GOLFS: Feature Selection via Combining Both Global and Local Information for High Dimensional Clustering

Multi-view clustering based on principal component analysis and binary pairwise fused penalty

Non-marginal feature screening for varying coefficient competing risks model

A covariate-driven beta-binomial integer-valued GARCH-type models for bounded counts with an application

Robust estimation of large factor models for tensor-valued time series

Automatic Change-Point Detection in Time Series via Deep Learning

Inference for ultra-high dimensional quasi-likelihood models

Simultaneous Statistical Inference for Second Order Parameters of Time Series under Weak Conditions

covariance test for discretely observed functional data

Estimation of Linear Functionals in High Dimensional Linear Models: From Sparsity to Non-sparsity

TBC

TBC

Professor Lai’s Contributions to Biopharmaceutical Industry and Regulatory Science

Open Forum Attribution by Audience

Testing Homogeneity in High Dimensional Data through Random Projections

A Unified Generalization of Inverse Regression Via Adaptive Column Selection

Semi-Distance Correlation and Its Applications

Weak approximation of nonlinear filtering for multiscale McKean-Vlasov stochastic systems

Weighted residual empirical processes, martingale transformations, and model checking for regressions