Kazuki Natori

J-GLOBAL         Last updated: Apr 3, 2019 at 14:46
 
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Name
Kazuki Natori
Affiliation
The University of Electro-Communications
Section
Graduate School of Informatics and Engineering, Department of Informatics and Network Engineering
Degree
Master of Engineering(The University of Electro-Communications)

Research Areas

 
 

Education

 
Apr 2016
 - 
Today
Department of Computer and Network Engineering, Graduate school of Informatics and Engineering, The University of Electro-Communications
 
Apr 2014
 - 
Mar 2016
Department of Social Intelligence and Informatics, Graduate school of Informatics and Systems, The University of Electro-Communications
 
Apr 2010
 - 
Mar 2014
Faculty of Informatics and Engineering, The University of Electro-Communications
 
Apr 2007
 - 
Mar 2010
Academic Course, Hikawa High School
 

Awards & Honors

 
Jul 2017
Consistent learning Bayesian networks with thousands variables, JSAI Annual Conference Student Incentive Award, The 31th Annual Conference of the Japan Society for Artificial Intelligence
 
Mar 2016
Constraint-based learning Bayesian networks using Bayes factor, 電気通信大学目黒会 目黒会賞, The University of Electro-Communications
 

Published Papers

 
Learning huge Bayesian networks by RAI algorithm using Bayes factor
Kazuki Natori, Masaki Uto, Maomi Ueno
THE INSTITUTE OF ELECTRONICS, INFORMATION AND COMMUNICATION ENGINEERS   D 754-768   May 2018   [Refereed]
Consistent Learning Bayesian Networks with Thousands of Variables
Kazuki Natori, Masaki Uto, and Maomi Ueno
Proc. of The 3rd International Workshop on Advanced Methodologies for Bayesian Networks, PMLR   73 57-68   Sep 2017   [Refereed]
Kazuki Natori, Masaki Uto, Yu Nishiyama, Shuichi Kawano, Maomi Ueno
Lecture Notes in Artificial Intelligence   9505 15-31   Jan 2016   [Refereed]

Conference Activities & Talks

 
Bayes factorを用いた制約ベースアプローチに基づく大規模ベイジアンネットワーク学習
Kazuki Natori, Masaki Uto, Maomi Ueno
46th annual meeting of the Behaviormetric Society   6 Sep 2018   
Bayes factorに基づくRAIアルゴリズムを用いた大規模ベイジアンネットワーク学習
Kazuki Natori, Masaki Uto, Maomi Ueno
The 20th Information-Based Induction Science Workshop (IBISML2017)   9 Nov 2017   
Consistent learning Bayesian networks with thousands variables
Kazuki Natori, Masaki Uto, and Maomi Ueno
The 31st Annual Conference of the Japanese Society for Artificial Intelligence, 2017   23 May 2017   
Bayes factorを用いた大規模ベイジアンネットワークの構築
Kazuki Natori, Masaki Uto, Maomi Ueno
The 19th Information-Based Induction Science Workshop (IBISML2016)   16 Nov 2016   
Learning Bayesian networks: Recursive autonomy identification algorithm incorporating a strict learning
Natori, K., Uto, M., Nishiyama, Y., Kawano, S., and Ueno, M.
数学協働プログラム 確率的グラフィカルモデル   19 Mar 2015