23 citations · 50 across the 6 of their papers we have counts for
3 papers · 1 filter
On Random Subsampling of Gaussian Process Regression: A Graphon-Based Analysis
Kohei Hayashi, Masaaki Imaizumi, Yuichi Yoshida
In this paper, we study random subsampling of Gaussian process regression, one of the simplest approximation baselines, from a theoretical perspective. Although subsampling discard…
On Tensor Train Rank Minimization: Statistical Efficiency and Scalable Algorithm
Masaaki Imaizumi, Takanori Maehara, Kohei Hayashi
Tensor train (TT) decomposition provides a space-efficient representation for higher-order tensors. Despite its advantage, we face two crucial limitations when we apply the TT deco…
Making Tree Ensembles Interpretable
Satoshi Hara, Kohei Hayashi
Tree ensembles, such as random forest and boosted trees, are renowned for their high prediction performance, whereas their interpretability is critically limited. In this paper, we…