25 citations · 88 across the 20 of their papers we have counts for
21 papers
On the Asymptotics of Item Selection in Multidimensional Computerized Adaptive Testing
Seungwon Lee, Xiaoou Li
We study Fisher-information-based item-selection rules for multidimensional computerized adaptive testing (MCAT) with intentional and nuisance abilities. Although such rules are wi…
Sequential Change Point Detection with FDR Control in Reconfigurable Sensor Networks
Seungwon Lee, Yunxiao Chen, Xiaoou Li
This paper investigates sequential change-point detection in reconfigurable sensor networks. In this problem, data from multiple sensors are observed sequentially. Each sensor can…
A Latent Variable Model with Change-Points and Its Application to Time Pressure Effects in Educational Assessment
Gabriel Wallin, Yunxiao Chen, Yi-Hsuan Lee +1
Educational assessments are valuable tools for measuring student knowledge and skills, but their validity can be compromised when test takers exhibit changes in response behavior d…
A Generalized Latent Factor Model Approach to Mixed-data Matrix Completion with Entrywise Consistency
Yunxiao Chen, Xiaoou Li
Matrix completion is a class of machine learning methods that concerns the prediction of missing entries in a partially observed matrix. This paper studies matrix completion for mi…
Optimal Parallel Sequential Change Detection under Generalized Performance Measures
Zexian Lu, Yunxiao Chen, Xiaoou Li
This paper considers the detection of change points in parallel data streams, a problem widely encountered when analyzing large-scale real-time streaming data. Each stream may have…
Item Response Theory -- A Statistical Framework for Educational and Psychological Measurement
Yunxiao Chen, Xiaoou Li, Jingchen Liu +1
Item response theory (IRT) has become one of the most popular statistical models for psychometrics, a field of study concerned with the theory and techniques of psychological measu…
Determining the Number of Factors in High-dimensional Generalized Latent Factor Models
Yunxiao Chen, Xiaoou Li
As a generalization of the classical linear factor model, generalized latent factor models are useful for analyzing multivariate data of different types, including binary choices a…
A Note on Exploratory Item Factor Analysis by Singular Value Decomposition
Haoran Zhang, Yunxiao Chen, Xiaoou Li
We revisit a singular value decomposition (SVD) algorithm given in Chen et al. (2019b) for exploratory Item Factor Analysis (IFA). This algorithm estimates a multidimensional IFA m…
Spherical Regression under Mismatch Corruption with Application to Automated Knowledge Translation
Xu Shi, Xiaoou Li, Tianxi Cai
Motivated by a series of applications in data integration, language translation, bioinformatics, and computer vision, we consider spherical regression with two sets of unit-length…
Structured Latent Factor Analysis for Large-scale Data: Identifiability, Estimability, and Their Implications
Yunxiao Chen, Xiaoou Li, Siliang Zhang
Latent factor models are widely used to measure unobserved latent traits in social and behavioral sciences, including psychology, education, and marketing. When used in a confirmat…
Joint Maximum Likelihood Estimation for High-dimensional Exploratory Item Response Analysis
Yunxiao Chen, Xiaoou Li, Siliang Zhang
Joint maximum likelihood (JML) estimation is one of the earliest approaches to fitting item response theory (IRT) models. This procedure treats both the item and person parameters…
Asymptotically Optimal Sequential Design for Rank Aggregation
Xi Chen, Yunxiao Chen, Xiaoou Li
A sequential design problem for rank aggregation is commonly encountered in psychology, politics, marketing, sports, etc. In this problem, a decision maker is responsible for ranki…
Uniformly Efficient Simulation for Extremes of Gaussian Random Fields
Xiaoou Li, Gongjun Xu
This paper considers the problem of simultaneously estimating rare-event probabilities for a class of Gaussian random fields. A conventional rare-event simulation method is usually…
Optimal Stopping and Worker Selection in Crowdsourcing: an Adaptive Sequential Probability Ratio Test Framework
Xiaoou Li, Yunxiao Chen, Xi Chen +2
In this paper, we aim at solving a class of multiple testing problems under the Bayesian sequential decision framework. Our motivating application comes from binary labeling tasks…
Moderate Deviation for Random Elliptic PDEs with Small Noise
Xiaoou Li, Jingchen Liu, Jianfeng Lu +1
Partial differential equations with random inputs have become popular models to characterize physical systems with uncertainty coming from, e.g., imprecise measurement and intrinsi…
A Fused Latent and Graphical Model for Multivariate Binary Data
Yunxiao Chen, Xiaoou Li, Jingchen Liu +1
We consider modeling, inference, and computation for analyzing multivariate binary data. We propose a new model that consists of a low dimensional latent variable component and a s…
Chernoff Index for Cox Test of Separate Parametric Families
Xiaoou Li, Jingchen Liu, Zhiliang Ying
The asymptotic efficiency of a generalized likelihood ratio test proposed by Cox is studied under the large deviations framework for error probabilities developed by Chernoff. In p…
A Multilevel Approach towards Unbiased Sampling of Random Elliptic Partial Differential Equations
Xiaoou Li, Jingchen Liu
Partial differential equation is a powerful tool to characterize various physics systems. In practice, measurement errors are often present and probability models are employed to a…
Sequential Hypothesis Test with Online Usage-Constrained Sensor Selection
Shang Li, Xiaoou Li, Xiaodong Wang +1
This work investigates the sequential hypothesis testing problem with online sensor selection and sensor usage constraints. That is, in a sensor network, the fusion center sequenti…
Decentralized Sequential Composite Hypothesis Test Based on One-Bit Communication
Shang Li, Xiaoou Li, Xiaodong Wang +1
This paper considers the sequential composite hypothesis test with multiple sensors. The sensors observe random samples in parallel and communicate with a fusion center, who makes…
Rare-event Simulation and Efficient Discretization for the Supremum of Gaussian Random Fields
Xiaoou Li, Jingchen Liu
In this paper, we consider a classic problem concerning the high excursion probabilities of a Gaussian random field living on a compact set . We develop efficient computatio…