Search Results for author:
Found 6 papers, 1 papers with code
Bayesian Optimization for Cascade-type Multi-stage Processes
A cascade process is a multistage process in which the output of one stage is used as an input for the subsequent stage.
Active learning for distributionally robust level-set estimation
A natural measure of robustness is the probability that $f(\bm x, \bm w)$ exceeds a given threshold $h$, which is known as the \emph{probability threshold robustness} (PTR) measure in the literature on robust optimization.
Quantifying Statistical Significance of Neural Network-based Image Segmentation by Selective Inference
To overcome this difficulty, we introduce a conditional selective inference (SI) framework -- a new statistical inference framework for data-driven hypotheses that has recently received considerable attention -- to compute exact (non-asymptotic) valid p-values for the segmentation results.
Mean-Variance Analysis in Bayesian Optimization under Uncertainty
As an AL problem in such an uncertain environment, we study Mean-Variance Analysis in Bayesian Optimization (MVA-BO) setting.
Bayesian Quadrature Optimization for Probability Threshold Robustness Measure
In many product development problems, the performance of the product is governed by two types of parameters called design parameter and environmental parameter.
Bayesian Experimental Design for Finding Reliable Level Set under Input Uncertainty
In the manufacturing industry, it is often necessary to repeat expensive operational testing of machine in order to identify the range of input conditions under which the machine operates properly.
