research
∙
09/03/2023
A Bootstrap Hypothesis Test for High-Dimensional Mean Vectors
This paper is concerned with testing global null hypotheses about popula...
share
research
∙
08/29/2023
Inferences on Mixing Probabilities and Ranking in Mixed-Membership Models
Network data is prevalent in numerous big data applications including ec...
research
∙
08/05/2023
Spectral Ranking Inferences based on General Multiway Comparisons
This paper studies the performance of the spectral method in the estimat...
research
∙
06/28/2023
UTOPIA: Universally Trainable Optimal Prediction Intervals Aggregation
Uncertainty quantification for prediction is an intriguing problem with ...
research
∙
04/21/2023
The Isotonic Mechanism for Exponential Family Estimation
In 2023, the International Conference on Machine Learning (ICML) require...
research
∙
04/14/2023
Minimax-Optimal Reward-Agnostic Exploration in Reinforcement Learning
This paper studies reward-agnostic exploration in reinforcement learning...
research
∙
03/02/2023
On the Provable Advantage of Unsupervised Pretraining
Unsupervised pretraining, which learns a useful representation using a l...
research
∙
02/23/2023
Communication-Efficient Distributed Estimation and Inference for Cox's Model
Motivated by multi-center biomedical studies that cannot share individua...
research
∙
02/12/2023
Deep Neural Networks for Nonparametric Interaction Models with Diverging Dimension
Deep neural networks have achieved tremendous success due to their repre...
research
∙
12/20/2022
Uncertainty Quantification of MLE for Entity Ranking with Covariates
This paper concerns with statistical estimation and inference for the ra...
research
∙
11/22/2022
Robust High-dimensional Tuning Free Multiple Testing
A stylized feature of high-dimensional data is that many variables have ...
research
∙
11/22/2022
Ranking Inferences Based on the Top Choice of Multiway Comparisons
This paper considers ranking inference of n items based on the observed ...
research
∙
10/31/2022
SIMPLE-RC: Group Network Inference with Non-Sharp Nulls and Weak Signals
Large-scale network inference with uncertainty quantification has import...
research
∙
10/05/2022
Factor Augmented Sparse Throughput Deep ReLU Neural Networks for High Dimensional Regression
This paper introduces a Factor Augmented Sparse Throughput (FAST) model ...
research
∙
10/03/2022
Factor-Augmented Regularized Model for Hazard Regression
A prevalent feature of high-dimensional data is the dependence among cov...
research
∙
09/25/2022
Simultaneous Estimation and Group Identification for Network Vector Autoregressive Model with Heterogeneous Nodes
We study the dynamic behaviors of heterogeneous individuals observed in ...
research
∙
08/23/2022
Strategic Decision-Making in the Presence of Information Asymmetry: Provably Efficient RL with Algorithmic Instruments
We study offline reinforcement learning under a novel model called strat...
research
∙
06/09/2022
Robust Matrix Completion with Heavy-tailed Noise
This paper studies low-rank matrix completion in the presence of heavy-t...
research
∙
06/08/2022
Model-Based Reinforcement Learning Is Minimax-Optimal for Offline Zero-Sum Markov Games
This paper makes progress towards learning Nash equilibria in two-player...
research
∙
03/20/2022
How do noise tails impact on deep ReLU networks?
This paper investigates the stability of deep ReLU neural networks for n...
research
∙
03/14/2022
The Efficacy of Pessimism in Asynchronous Q-Learning
This paper is concerned with the asynchronous form of Q-learning, which ...
research
∙
03/02/2022
Are Latent Factor Regression and Sparse Regression Adequate?
We propose the Factor Augmented sparse linear Regression Model (FARM) th...
research
∙
11/14/2021
Curriculum Learning for Vision-and-Language Navigation
Vision-and-Language Navigation (VLN) is a task where an agent navigates ...
research
∙
11/05/2021
Negative Sample is Negative in Its Own Way: Tailoring Negative Sentences for Image-Text Retrieval
Matching model is essential for Image-Text Retrieval framework. Existing...
research
∙
09/13/2021
Policy Optimization Using Semiparametric Models for Dynamic Pricing
In this paper, we study the contextual dynamic pricing problem where the...
research
∙
09/12/2021
Constructing Phrase-level Semantic Labels to Form Multi-Grained Supervision for Image-Text Retrieval
Existing research for image text retrieval mainly relies on sentence-lev...
research
∙
09/11/2021
Factor and Idiosyncratic VAR-Ito Volatility Models for Heavy-Tailed High-Frequency Financial Data
Various parametric models have been developed to predict large volatilit...
research
∙
08/03/2021
Optimal Covariate Balancing Conditions in Propensity Score Estimation
Inverse probability of treatment weighting (IPTW) is a popular method fo...
research
∙
07/26/2021
Inference for Heteroskedastic PCA with Missing Data
This paper studies how to construct confidence regions for principal com...
research
∙
07/06/2021
A provable two-stage algorithm for penalized hazards regression
From an optimizer's perspective, achieving the global optimum for a gene...
research
∙
05/28/2021
Sample-Efficient Reinforcement Learning for Linearly-Parameterized MDPs with a Generative Model
The curse of dimensionality is a widely known issue in reinforcement lea...
research
∙
02/25/2021
Adaptive Robust Large Volatility Matrix Estimation Based on High-Frequency Financial Data
Several novel statistical methods have been developed to estimate large ...
research
∙
02/22/2021
Bridging factor and sparse models
Factor and sparse models are two widely used methods to impose a low-dim...
research
∙
01/06/2021
The Interplay of Demographic Variables and Social Distancing Scores in Deep Prediction of U.S. COVID-19 Cases
With the severity of the COVID-19 outbreak, we characterize the nature o...
research
∙
12/15/2020
Spectral Methods for Data Science: A Statistical Perspective
Spectral methods have emerged as a simple yet surprisingly effective app...
research
∙
11/08/2020
Do We Exploit all Information for Counterfactual Analysis? Benefits of Factor Models and Idiosyncratic Correction
The measurement of treatment (intervention) effects on a single (or just...
research
∙
09/21/2020
Recent Developments on Factor Models and its Applications in Econometric Learning
This paper makes a selective survey on the recent development of the fac...
research
∙
08/04/2020
Convex and Nonconvex Optimization Are Both Minimax-Optimal for Noisy Blind Deconvolution
We investigate the effectiveness of convex relaxation and nonconvex opti...
research
∙
07/24/2020
Canonical thresholding for non-sparse high-dimensional linear regression
We consider a high-dimensional linear regression problem. Unlike many pa...
research
∙
07/16/2020
Understanding Implicit Regularization in Over-Parameterized Nonlinear Statistical Model
We study the implicit regularization phenomenon induced by simple optimi...
research
∙
07/10/2020
Community Network Auto-Regression for High-Dimensional Time Series
Modeling responses on the nodes of a large-scale network is an important...
research
∙
07/05/2020
Semiparametric Tensor Factor Analysis by Iteratively Projected SVD
This paper introduces a general framework of Semiparametric TEnsor FActo...
research
∙
07/03/2020
When is best subset selection the "best"?
Best subset selection (BSS) is fundamental in statistics and machine lea...
research
∙
06/24/2020
An ℓ_p theory of PCA and spectral clustering
Principal Component Analysis (PCA) is a powerful tool in statistics and ...
research
∙
06/23/2020
Bootstrapping ℓ_p-Statistics in High Dimensions
This paper considers a new bootstrap procedure to estimate the distribut...
research
∙
02/23/2020
Hypothesis testing for eigenspaces of covariance matrix
Eigenspaces of covariance matrices play an important role in statistical...
research
∙
01/15/2020
Bridging Convex and Nonconvex Optimization in Robust PCA: Noise, Outliers, and Missing Data
This paper delivers improved theoretical guarantees for the convex progr...
research
∙
01/07/2020
Statistical Inference for High-Dimensional Matrix-Variate Factor Model
This paper considers the estimation and inference of factor loadings, la...
research
∙
10/03/2019
SIMPLE: Statistical Inference on Membership Profiles in Large Networks
Network data is prevalent in many contemporary big data applications in ...
research
∙
09/24/2019