3 citations · 5 across the 8 of their papers we have counts for
10 papers
Cumulant-based approximation for fast and efficient prediction for species distribution
Osamu Komori, Yusuke Saigusa, Shinto Eguchi +1
Species distribution modeling plays an important role in estimating the habitat suitability of species using environmental variables. For this purpose, Maxent and the Poisson point…
Robust minimum divergence estimation in a spatial Poisson point process
Yusuke Saigusa, Shinto Eguchi, Osamu Komori
Species distribution modeling (SDM) plays a crucial role in investigating habitat suitability and addressing various ecological issues. While likelihood analysis is commonly used t…
Statistical learning for species distribution models in ecological studies
Osamu Komori, Yusuke Saigusa, Shinto Eguchi
We discuss species distribution models (SDM) for biodiversity studies in ecology. SDM plays an important role to estimate abundance of a species based on environmental variables th…
Active Learning by Query by Committee with Robust Divergences
Hideitsu Hino, Shinto Eguchi
Active learning is a widely used methodology for various problems with high measurement costs. In active learning, the next object to be measured is selected by an acquisition func…
Minimum information divergence of Q-functions for dynamic treatment resumes
Shinto Eguchi
This paper aims at presenting a new application of information geometry to reinforcement learning focusing on dynamic treatment resumes. In a standard framework of reinforcement le…
Robust self-tuning semiparametric PCA for contaminated elliptical distribution
Hung Hung, Su-Yun Huang, Shinto Eguchi
Principal component analysis (PCA) is one of the most popular dimension reduction methods. The usual PCA is known to be sensitive to the presence of outliers, and thus many robust…