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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 6 of 6  /   
Committee Date Time Place Paper Title / Authors Abstract Paper #
IT 2022-07-22
14:15		 Okayama Okayama University of Science
(Primary: On-site, Secondary: Online)		 A Study on Multilevel Coefficient Linear Regression Model and an Optimal Prediction for Multilevel Data by Bayes Decision Theory
Kohei Horinouchi, Naoki Ichijo, Taisuke Ishiwatari, Toshiyasu Matsushima (Waseda Univ.) IT2022-26		 It is common practice to apply Multilevel Model (Linear Mixed Model, Hierarchical Linear Model) for the data sampled fro... [more] IT2022-26
pp.56-60
IT 2022-07-22
14:40		 Okayama Okayama University of Science
(Primary: On-site, Secondary: Online)		 Meta-Tree Set Construction for Approximate Bayes Optimal Prediction on Decision Tree Model
Keito Tajima, Naoki Ichijo, Koshi Shimada, Toshiyasu Matsushima (Waseda Univ.) IT2022-27		 Decision trees are generally used as a predictive function, but some studies use decision trees as data-generative model... [more] IT2022-27
pp.61-66
IT 2022-07-22
15:05		 Okayama Okayama University of Science
(Primary: On-site, Secondary: Online)		 Bayes Optimal Approximation Algorithm by Boosting-like Construction of Meta-Tree Sets in Classification on Decision Tree Model
Ryota Maniwa, Naoki Ichijo, Koshi Shimada, Toshiyasu Matsushima (Waseda Univ.) IT2022-28		 Decision trees are used for classification and regression such as predicting the objective variable corresponding to the... [more] IT2022-28
pp.67-72
IBISML 2022-03-08
11:20		 Online Online Tree-Structured Generative Model with Latent Variables and Approximate Variational Bayesian Inference
Naoki Ichijo, Yuta Nakahara (Waseda Univ.), Shota Saito (Gunma Univ.), Toshiyasu Matsushima (Waseda Univ.) IBISML2021-33		  [more] IBISML2021-33
pp.19-26
RCS, SIP, IT 2022-01-21
09:00		 Online Online An Approximation by Meta-Tree Boosting Method to Bayesian Optimal Prediction for Decision Tree Model
Wenbin Yu, Koki Kazama, Yuta Nakahara, Naoki Ichijo (Waseda Univ.), Shota Saito (Gunma Univ.), Toshiyasu Matsushima (Waseda Univ.) IT2021-67 SIP2021-75 RCS2021-235		  [more] IT2021-67 SIP2021-75 RCS2021-235
pp.219-224
IT 2020-12-02
10:00		 Online Online Policy Optimization Based on Bayesian Decision Theory in Learning Period on Markov Decision Process
Naoki Ichijo, Yuta Nakahara, Yuto Motomura, Toshiyasu Matsushima (Waseda Univ.) IT2020-31		 In Markov decision process(MDP) problems with an unknown transition probability, a learning agent has to learn the unkno... [more] IT2020-31
pp.38-43
 Results 1 - 6 of 6  /   
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