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01/20/2023
Active Learning of Piecewise Gaussian Process Surrogates
Active learning of Gaussian process (GP) surrogates has been useful for ...
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04/13/2021
Gaussian Process Model for Estimating Piecewise Continuous Regression Functions
This paper presents a Gaussian process (GP) model for estimating piecewi...
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08/25/2020
Data Science for Motion and Time Analysis with Modern Motion Sensor Data
The motion-and-time analysis has been a popular research topic in operat...
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08/25/2020
Variable selection for Gaussian process regression through a sparse projection
This paper presents a new variable selection approach integrated with Ga...
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01/14/2020
Robust Gaussian Process Regression with a Bias Model
This paper presents a new approach to a robust Gaussian process (GP) reg...
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11/03/2019
Gaussian process metamodeling for experiments with manipulating factors
This paper presents a new Gaussian process (GP) metamodeling approach fo...
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04/02/2019
Sequential Adaptive Design for Jump Regression Estimation
Selecting input data or design points for statistical models has been of...
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01/23/2017
Patchwork Kriging for Large-scale Gaussian Process Regression
This paper presents a new approach for Gaussian process (GP) regression ...
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11/24/2016
Two-Level Structural Sparsity Regularization for Identifying Lattices and Defects in Noisy Images
This paper presents a regularized regression model with a two-level stru...
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09/26/2016
Robust Regression For Image Binarization Under Heavy Noises and Nonuniform Background
This paper presents a robust regression approach for image binarization ...
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08/04/2016