1 citations · 1 across the 2 of their papers we have counts for
3 papers
stat.ME2022★ 1 cited
Bayesian Fused Lasso Modeling via Horseshoe Prior
Yuko Kakikawa, Kaito Shimamura, Shuichi Kawano
Bayesian fused lasso is one of the sparse Bayesian methods, which shrinks both regression coefficients and their successive differences simultaneously. In this paper, we propose a…
stat.ME2021
A Bayesian approach to multi-task learning with network lasso
Kaito Shimamura, Shuichi Kawano
Network lasso is a method for solving a multi-task learning problem through the regularized maximum likelihood method. A characteristic of network lasso is setting a different mode…
stat.ML2019
Bayesian sparse convex clustering via global-local shrinkage priors
Kaito Shimamura, Shuichi Kawano
Sparse convex clustering is to cluster observations and conduct variable selection simultaneously in the framework of convex clustering. Although a weighted norm is usually e…