Computation, Structure, and Learning

Our group, led by Assoc. Prof. Mahito Sugiyama, studies machine learning at National Institute of Informatics (NII) in Tokyo since 2017.

Machine learning is the discipline of studying intelligent computing systems, which nowadays plays a key role in artificial intelligence (AI). To reveal the nature of learning, we focus on the relationship between computational processes, discrete structures, and machine learning models.

We belong to the Department of Informatics, SOKENDAI (The Graduate University for Advanced Studies), which offers 3-year and 5-year Ph.D. courses. More information is available at the NII website.


  • Zhanpeng Zhou from Shanghai Jiao Tong University joined our lab as an internship student (Sep. 27, 2023).
  • Masatsugu Yamada received his Ph.D. degree in Informatics from SOKENDAI. Congratulations! (Sep. 26, 2023)
  • Our paper "Many-body Approximation for Non-negative Tensors" (First author: Kazu Ghalamkari) has been accepted to NeurIPS 2023 (Sep. 22, 2023).   [arXiv]
  • Our paper "Unsupervised Tensor Based Feature Extraction from Multivariate Time Series" (First author: Kiyotaka Matsue) has been accepted to IEEE Access (Sep. 21, 2023).
  • Two papers have been accepted to ICML 2023 workshops (Differentiable Almost Everything and Duality Principles for Modern ML) (Jun. 22, 2023).
  • Our paper "How Graph Features from Message Passing Affect Graph Classification and Regression?" (First author: Masatsugu Yamada) has been accepted to Intelligent Data Analysis (Jun. 13, 2023).
  • Our paper "Molecular Graph Generation by Decomposition and Reassembling" (First author: Masatsugu Yamada) has been accepted to ACS Omega (Apr. 10, 2023).   [arXiv]
  • Yuichi Maruyama joined our lab as a new Ph.D. student (Apr. 1, 2023).

more news...


National Institute of Informatics,
2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo 101-8430, Japan
Email: mahito (at)

© Mahito Sugiyama 2023