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Godai Azuna

Master's Degree Program Student

Department of Mathematical and Computing Science,
School of Computing,
Tokyo Institute of Technology.

E-mail
godai0519 [at] gmail.com
azuma.g.aa [at] m.titech.ac.jp

Education

Present
Department of Mathematical and Computing Science,
Tokyo Institute of Technology (Master's course)
B. Engineering
Department of Communication Engineering and Informatics,
The University of Electro-Communications (2018)
Assoc. Engineering
Department of Computer Science,
National Institute of Technology, Tokyo College (2016)

Softwares

BayesianNetwork
Framework for learning and reasoning Bayesian Networks, written in C++14.
twit-library
OAuth1.0 client library in C++11, powered by BoostConnect.
BoostConnect
Server/Client framework wrapping Boost.Asio (You should try to use cpp-netlib and Networking TS).
Window Changer
Utility software which associates keyboards with a unique window, and actives associated window when pressing keyboard.

Refereed Conference Papers (査読付き会議発表論文)

  1. Godai Azuma, Daisuke Kitakoshi, and Masato Suzuki,
    Stepwise Structure Learning Using Probabilistic Pruning for Bayesian Networks: Improving Efficiency and Comparing Characteristics.
    Information Science and Applications 2017 (ICISA 2017),
    Lecture Notes in Electrical Engineering 424 (2017), pp. 533–543.
    DOI: 10.1007/978-981-10-4154-9_62.

Oral presentations (学会・研究会発表)

  1. 東 悟大, 北越 大輔, and 鈴木 雅人,
    確率的枝刈りを用いたベイジアンネットの構造学習法の高速化.
    電子情報通信学会 2016年総合大会講演論文集 (IEICE2016), D-20-8, 2016, pp. 208.
  2. 北越 大輔, 東 悟大, and 鈴木 雅人,
    ベイジアンネットの段階的構造学習法に対する確率的枝刈りを用いた高速化について.
    情報処理学会研究報告 知能システム (ICS), 2016-ICS-182 (2), 2016, pp. 1–8.
  3. 東 悟大, 北越 大輔, and 鈴木 雅人,
    クラスタリングと確率的枝刈りを用いたベイジアンネットの段階的構造学習法 −確率的枝刈りの性能改善および特性評価−.
    計測自動制御学会 システム・情報部門 学術講演会 2015, SS4-1, 2015, pp. 666–671.

Presentation materials (発表資料)

  1. 闇鍋の中に投げ込むDartの矢, 闇鍋プログラミング勉強会, 03/2012.