13 citations · 52 across the 18 of their papers we have counts for
4 papers · 1 filter
More Powerful Selective Kernel Tests for Feature Selection
Jen Ning Lim, Makoto Yamada, Wittawat Jitkrittum +3
Refining one's hypotheses in the light of data is a common scientific practice; however, the dependency on the data introduces selection bias and can lead to specious statistical a…
Fast generalization error bound of deep learning without scale invariance of activation functions
Yoshikazu Terada, Ryoma Hirose
In theoretical analysis of deep learning, discovering which features of deep learning lead to good performance is an important task. In this paper, using the framework for analyzin…
Selective inference after feature selection via multiscale bootstrap
Yoshikazu Terada, Hidetoshi Shimodaira
It is common to show the confidence intervals or -values of selected features, or predictor variables in regression, but they often involve selection bias. The selective inferen…
Selective Inference for Testing Trees and Edges in Phylogenetics
Hidetoshi Shimodaira, Yoshikazu Terada
Selective inference is considered for testing trees and edges in phylogenetic tree selection from molecular sequences. This improves the previously proposed approximately unbiased…