Shogo Hayashi's Home Page
Shogo Hayashi
Ph.D. Student
Department of Intelligence Science and Technology, Graduate School of Informatics, Kyoto University, Japan
Machine Learning and Data Mining Research Laboratory
Email: hayashi, at, ml.ist.i.kyoto-u.ac.jp
Supervisor: Hisashi Kashima
Curriculum Vitae (updated Jun. 2020)
Research Interest
Machine Learning, Bayesian Optimization, Change-Point Detection
Research Experience
- Research Assistant, Center for Advanced Intelligence Project (AIP), RIKEN (May 2017 – present)
- Research Fellowship, Japan Society for the Promotion of Science, Research Fellowship for Young Scientists DC2 (Apr. 2018 - Mar. 2020)
- Research Intern, Probabilistic Numerics Group, Max Planck Institute for Intelligent Systems (Jul. 2018 - Oct. 2018)
- Research Intern, Data Science Research Laboratory, NEC Corporation (Oct. 2017 - Dec. 2017)
- Engineer Intern, Ikkyo Tech Inc (current, AlpacaDB) (Aug. 2013 - Oct. 2013)
Education
- Ph.D student
Department of Intelligence Science and Technology, Graduate School of Informatics, Kyoto University, Japan (Apr. 2017 - present)
Research Topic: Machine Learning Using Additinal Information for Expensive-to-evaluate Small Data
Supervisor: Prof. Hisashi Kashima
- Master’s Degree in Computer Science
Department of Information and Physical Sciences, Graduate School of Information Science and Technology, Osaka University, Japan (Apr. 2015. - Mar. 2017)
Master Thesis: Error Detection in Ocean Data Considering Spatial Autocorrelation
Supervisor: Associate Prof. Ken-ichi Fukui
- Bachelor’s Degree in Engineering
Applied Physics Course, School of Engineering, Osaka University, Japan (Apr. 2011 - Mar. 2015)
Bachelor Thesis: Viscoelasticity Measurement Using Brillouin Scattering
Supervisor: Prof. Yasushi Inoue
Publication
Journal (refereed)
- Shogo Hayashi, Yoshinobu Kawahara, Hisashi Kashima: Active Change-Point Detection, The Japanese Society for Artificial Intelligence, Vol. 35, No. 5, pp. E-JA10_1-10, 2020.
- Shogo Hayashi, Akira Tanimoto, Hisashi Kashima: Long-Term Prediction of Small Time-Series Data Using Generalized Distillation, The Japanese Society for Artificial Intelligence, Vol. 35, No. 5, pp. B-K33_1-9, 2020.
- Shogo Hayashi, Satoshi Ono, Shigeki Hosoda, Masayuki Numao, Ken-ichi Fukui: Error Detection in Ocean Data Considering Spatial Autocorrelation, The Japanese Society for Artificial Intelligence, Vol. 33, No. 2, pp. D-SGAI02_1-10, 2018.
International Conference (refereed)
- Shogo Hayashi, Yoshinobu Kawahara, Hisashi Kashima: Active Change-Point Detection, in Proceedings of The 10th Asian Conference on Machine Learning, Nagoya, Japan, Nov. 2019. (acceptance rate: 25.4%)
- Shogo Hayashi, Akira Tanimoto, Hisashi Kashima: Long-Term Prediction of Small Time-Series Data Using Generalized Distillation, in Proceedings of International Joint Conference on Neural Networks, Budapest, Hungary, July 14-19, 2019. (acceptance rate: 52.4%)
- Shogo Hayashi, Satoshi Ono, Shigeki Hosoda, Masayuki Numao, Ken-ichi Fukui: Error Detection of Ocean Depth Series Data with Area Partitioning and Using Sliding Window, in Proceedings of The 15th IEEE International Conference on Machine Learning and Applications, pp.1029-1033, Anaheim, USA, Dec. 2016. (acceptance rate: 31.98%)
Conference (non-refereed)
- 林 勝悟, 鹿島 久嗣: 条件付き確率に従うクエリを用いたベイズ最適化, 第22回情報論的学習理論ワークショップ (IBIS), 名古屋, 2019年11月. (in Japanese)
- 林 勝悟, 金川 元信, 鹿島 久嗣: ベイズ的測度最適化, 第21回情報論的学習理論ワークショップ (IBIS), 札幌, 2018年11月. (in Japanese)
- 林 勝悟, 河原 吉伸, 鹿島 久嗣: 能動的変化点検知, 第20回情報論的学習理論ワークショップ (IBIS), 東京, 2017年11月. (in Japanese)
- 林 勝悟, 小野 智司, 細田 滋毅, 沼尾 正行, 福井 健一：空間的自己相関を考慮した海洋データのエラー検知, 第31回人工知能学会全国大会, 愛知県産業労働センター, 2017年5月. (in Japanese)
- Shogo Hayashi, Satoshi Ono, Shigeki Hosoda, Masayuki Numao, Ken-ichi Fukui: Error Detection of Ocean Depth Series Data with Area Partitioning and Using Sliding Window, Machine Learning Summer School, Arequipa, Peru, Aug. 2016.
- 林 勝悟, 小野 智司, 細田 滋毅, 沼尾 正行, 福井 健一：近傍法による海洋深度系列データのエラー検知, 第26回インテリジェント・システム・シンポジウム, 大阪大学, 2016年10月. (in Japanese)
- 林 勝悟, 小野 智司, 細田 滋毅, 沼尾 正行, 福井 健一：クラスタリングによる海洋データの構造視覚化, 情報処理学会 第108回数理モデル化と問題解決研究会, Vol.2016-MPS-108, No.23, pp.1-6, 沖縄科学技術大学院大学, 2016年7月. (in Japanese)
Honor and Scholarship
- Student Presentation Award (学生優秀プレゼンテーション賞): 林 勝悟, 鹿島 久嗣: 条件付き確率に従うクエリを用いたベイズ最適化, 第22回情報論的学習理論ワークショップ (IBIS), 名古屋, 2019年11月. (in Japanese)
- Best Paper Award (最優秀論文賞): 林 勝悟, 小野 智司, 細田 滋毅, 沼尾 正行, 福井 健一：近傍法による海洋深度系列データのエラー検知, 第26回インテリジェント・システム・シンポジウム, 大阪大学, 2016年10月. (in Japanese)
- Scholarship: Cross-Boundary Innovation Program, Osaka University (Apr. 2015 - Mar. 2017)
Skill
Langage
- Japanese: Native
- English: Fluent (IELTS Band Score 5.5, Nov. 2016.)
Programming Langage
Miscellaneous
Other Activity
- Machine Learning Summer School, Arequipa, Peru (2-13 Aug. 2016)
- Field Study, Marshall Islands (2 weeks, May 2016)
- Study Abroad, Monash University (Aug. 2015)
- Cross-Boundary Innovation Program, Osaka University (Apr. 2015 - Mar. 2017)
- Field Study, Bangladesh (2 weeks Aug. 2013)
- Field Study, Phillipines (2 weeks, Mar. 2012)
Hobby
- Skateboard
- Cooking
- Japanese Green Tea