3 papers
stat.ME2026
Groupwise Predictor Envelope Models for Multivariate Linear Regression
Sota Osumi, Akira Okazaki, Shuichi Kawano
Envelope methods improve estimation efficiency in multivariate analysis by isolating low-dimensional structures that contain all the information material to the parameter of intere…
stat.ME2026
Variable Fusion and Selection via a Spike-and-Slab Approach with Nonlocal Priors
Junya Miyake, Akira Okazaki, Shuichi Kawano
Variable fusion in linear regression models is a statistical method that identifies covariates making similar contributions to the response variable and imposes the same coefficien…
stat.ME2024
Multi-task learning via robust regularized clustering with non-convex group penalties
Akira Okazaki, Shuichi Kawano
Multi-task learning (MTL) aims to improve estimation and prediction performance by sharing common information among related tasks. One natural assumption in MTL is that tasks are c…