11 citations · 15 across the 15 of their papers we have counts for
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stat.ML2024
Variational Bayesian Methods for a Tree-Structured Stick-Breaking Process Mixture of Gaussians by Application of the Bayes Codes for Context Tree Models
Yuta Nakahara
The tree-structured stick-breaking process (TS-SBP) mixture model is a non-parametric Bayesian model that can represent tree-like hierarchical structures among the mixture componen…
stat.ML2024★ 1 cited
Boosting-Based Sequential Meta-Tree Ensemble Construction for Improved Decision Trees
Ryota Maniwa, Naoki Ichijo, Yuta Nakahara +1
A decision tree is one of the most popular approaches in machine learning fields. However, it suffers from the problem of overfitting caused by overly deepened trees. Then, a meta-…
stat.ML2021
Probability Distribution on Full Rooted Trees
Yuta Nakahara, Shota Saito, Akira Kamatsuka +1
The recursive and hierarchical structure of full rooted trees is applicable to represent statistical models in various areas, such as data compression, image processing, and machin…