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08/18/2023
On Block Cholesky Decomposition for Sparse Inverse Covariance Estimation
The modified Cholesky decomposition is popular for inverse covariance es...
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04/18/2023
Bayesian D-Optimal Design of Experiments with Quantitative and Qualitative Responses
Systems with both quantitative and qualitative responses are widely enco...
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10/10/2022
Bayesian Sparse Regression for Mixed Multi-Responses with Application to Runtime Metrics Prediction in Fog Manufacturing
Fog manufacturing can greatly enhance traditional manufacturing systems ...
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09/17/2022
Neighborhood VAR: Efficient estimation of multivariate timeseries with neighborhood information
In data science, vector autoregression (VAR) models are popular in model...
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09/09/2022
Boosting Sensitivity of Large-scale Online Experimentation via Dropout Buyer Imputation
Metrics provide strong evidence to support hypotheses in online experime...
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09/06/2022
Modeling and Active Learning for Experiments with Quantitative-Sequence Factors
A new type of experiment that aims to determine the optimal quantities o...
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04/02/2022
A UCB-based Tree Search Approach to Joint Verification-Correction Strategy for Large Scale Systems
Verification planning is a sequential decision-making problem that speci...
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03/18/2022
EzGP: Easy-to-Interpret Gaussian Process Models for Computer Experiments with Both Quantitative and Qualitative Factors
Computer experiments with both quantitative and qualitative (QQ) inputs ...
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11/09/2021
Statistical Perspectives on Reliability of Artificial Intelligence Systems
Artificial intelligence (AI) systems have become increasingly popular in...
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10/17/2021
Building Degradation Index with Variable Selection for Multivariate Sensory Data
The modeling and analysis of degradation data have been an active resear...
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09/24/2021
A Parallel Tempering Approach for Efficient Exploration of the Verification Tradespace in Engineered Systems
Verification is a critical process in the development of engineered syst...
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05/14/2021
Robust Estimation of Sparse Precision Matrix using Adaptive Weighted Graphical Lasso Approach
Estimation of a precision matrix (i.e., inverse covariance matrix) is wi...
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04/04/2021
Efficient Experimental Design for Regularized Linear Models
Regularized linear models, such as Lasso, have attracted great attention...
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03/21/2021
On Efficient Design of Pilot Experiment for Generalized Linear Models
The experimental design for a generalized linear model (GLM) is importan...
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02/18/2021
A Generative Approach to Joint Modeling of Quantitative and Qualitative Responses
In many scientific areas, data with quantitative and qualitative (QQ) re...
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02/18/2021
JST-RR Model: Joint Modeling of Ratings and Reviews in Sentiment-Topic Prediction
Analysis of online reviews has attracted great attention with broad appl...
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01/06/2021
Sequential Design of Computer Experiments with Quantitative and Qualitative Factors in Applications to HPC Performance Optimization
Computer experiments with both qualitative and quantitative factors are ...
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08/14/2020
Bayesian Auxiliary Variable Model for Birth Records Data with Qualitative and Quantitative Responses
Many applications involve data with qualitative and quantitative respons...
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08/14/2020
A Maximin Φ_p-Efficient Design for Multivariate GLM
Experimental designs for a generalized linear model (GLM) often depend o...
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04/04/2020
Multivariate Regression of Mixed Responses for Evaluation of Visualization Designs
Information visualization significantly enhances human perception by gra...
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09/17/2018
Spatial Variable Selection and An Application to Virginia Lyme Disease Emergence
Lyme disease is an infectious disease that is caused by a bacterium call...
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06/11/2018
The CCP Selector: Scalable Algorithms for Sparse Ridge Regression from Chance-Constrained Programming
Sparse regression and variable selection for large-scale data have been ...
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01/17/2018
On I-Optimal Designs for Generalized Linear Models: An Efficient Algorithm via General Equivalence Theory
The generalized linear model plays an important role in statistical anal...
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01/01/2018
Ensemble Estimation of Large Sparse Covariance Matrix Based on Modified Cholesky Decomposition
Estimation of large sparse covariance matrices is of great importance fo...
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10/14/2017
