3 papers
stat.CO2026
Robust Global Fr'echet Regression via Weight Regularization
Hao Li, Shonosuke Sugasawa, Shota Katayama
The Fréchet regression is a useful method for modeling random objects in a general metric space given Euclidean covariates. However, the conventional approach could be sensitive t…
stat.ME2025
Empirical Bayes Method for Large Scale Multiple Testing with Heteroscedastic Errors
Kwangok Seo, Johan Lim, Kaiwen Wang +3
In this paper, we address the normal mean inference problem, which involves testing multiple means of normal random variables with heteroscedastic variances. Most existing empirica…
stat.CO2024
Adaptively Robust and Sparse K-means Clustering
Hao Li, Shonosuke Sugasawa, Shota Katayama
While K-means is known to be a standard clustering algorithm, its performance may be compromised due to the presence of outliers and high-dimensional noisy variables. This paper pr…