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02/03/2023
Randomized Gaussian Process Upper Confidence Bound with Tight Bayesian Regret Bounds
Gaussian process upper confidence bound (GP-UCB) is a theoretically prom...
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01/27/2023
Distributionally Robust Multi-objective Bayesian Optimization under Uncertain Environments
In this study, we address the problem of optimizing multi-output black-b...
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01/31/2022
Bayesian Optimization for Distributionally Robust Chance-constrained Problem
In black-box function optimization, we need to consider not only control...
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11/16/2021
Bayesian Optimization for Cascade-type Multi-stage Processes
Complex processes in science and engineering are often formulated as mul...
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10/18/2021
Valid and Exact Statistical Inference for Multi-dimensional Multiple Change-Points by Selective Inference
In this paper, we study statistical inference of change-points (CPs) in ...
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04/22/2021
Conditional Selective Inference for Robust Regression and Outlier Detection using Piecewise-Linear Homotopy Continuation
In practical data analysis under noisy environment, it is common to firs...
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02/08/2021
Active learning for distributionally robust level-set estimation
Many cases exist in which a black-box function f with high evaluation co...
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09/17/2020
Mean-Variance Analysis in Bayesian Optimization under Uncertainty
We consider active learning (AL) in an uncertain environment in which tr...
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06/22/2020
Bayesian Quadrature Optimization for Probability Threshold Robustness Measure
In many product development problems, the performance of the product is ...
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10/26/2019
Bayesian Experimental Design for Finding Reliable Level Set under Input Uncertainty
In the manufacturing industry, it is often necessary to repeat expensive...
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09/13/2019
Active learning for level set estimation under cost-dependent input uncertainty
As part of a quality control process in manufacturing it is often necess...
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06/03/2019
Computing Valid p-values for Image Segmentation by Selective Inference
Image segmentation is one of the most fundamental tasks of computer visi...
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03/08/2019