75 citations · 459 across the 65 of their papers we have counts for
9 papers · 1 filter
More Powerful and General Selective Inference for Stepwise Feature Selection using the Homotopy Continuation Approach
Kazuya Sugiyama, Vo Nguyen Le Duy, Ichiro Takeuchi
Conditional selective inference (SI) has been actively studied as a new statistical inference framework for data-driven hypotheses. The basic idea of conditional SI is to make infe…
Supervised sequential pattern mining of event sequences in sport to identify important patterns of play: an application to rugby union
Rory Bunker, Keisuke Fujii, Hiroyuki Hanada +1
Given a set of sequences comprised of time-ordered events, sequential pattern mining is useful to identify frequent subsequences from different sequences or within the same sequenc…
Quantifying Statistical Significance of Neural Network-based Image Segmentation by Selective Inference
Vo Nguyen Le Duy, Shogo Iwazaki, Ichiro Takeuchi
Although a vast body of literature relates to image segmentation methods that use deep neural networks (DNNs), less attention has been paid to assessing the statistical reliability…
Mean-Variance Analysis in Bayesian Optimization under Uncertainty
Shogo Iwazaki, Yu Inatsu, Ichiro Takeuchi
We consider active learning (AL) in an uncertain environment in which trade-off between multiple risk measures need to be considered. As an AL problem in such an uncertain environm…
Bayesian Quadrature Optimization for Probability Threshold Robustness Measure
Shogo Iwazaki, Yu Inatsu, Ichiro Takeuchi
In many product development problems, the performance of the product is governed by two types of parameters called design parameter and environmental parameter. While the former is…
Parametric Programming Approach for More Powerful and General Lasso Selective Inference
Vo Nguyen Le Duy, Ichiro Takeuchi
Selective Inference (SI) has been actively studied in the past few years for conducting inference on the features of linear models that are adaptively selected by feature selection…