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RIKEN Center for Advanced Intelligence Project Structured Learning Team

Team Leader: Yoshinobu Kawahara (D.Eng.)

Research Summary

Yoshinobu  Kawahara(D.Eng.)

When making predictions based on intelligent information processing such as machine learning, we usually have prior information about structures among variables in data. In our team, we study theories and algorithms for learning with such structural information. Moreover, we conduct applied researches by applying developed algorithms to a variety of scientific and engineering data.

Research Subjects:

  • Machine learning with structural prior information
  • Development of optimization algorithms for efficient learning
  • Learning for analysis of spatiotemporal dynamics
  • Application of developed methods to scientific and engineering data

Main Research Fields

  • Informatics

Related Research Fields

  • Engineering
  • Mathematical & Physical Sciences
  • Mathematical informatics
  • Statistical science
  • Intelligent informatics


  • Machine Learning
  • Data Science
  • Learning with Prior Information
  • Dynamics
  • Optimization

Selected Publications

  • 1.Fujii, K., Takeishi, N., Hojo, M., Inaba, Y., and Kawahara, Y.:
    "Physically-interpretable classification of network dynamics in complex collective motions"
    Scientific Reports, Vol.10, Article number 3005 (2020).
  • 2.Takeuchi, N., Yoshida, Y., and Kawahara, Y.:
    "Variational inference of penalized regression with submodular functions"
    Proceedings of the 35th Conference on Uncertainty in Artificial Intelligence (UAI'19), 443 (2019).
  • 3.Ishikawa, I., Fujii, K., Ikeda, M., Hashimoto, Y., and Kawahara, Y.:
    "Metric for nonlinear dynamical systems with Koopman operators"
    Advances in Neural Information Processing Systems 31, pp.2858-2868 (2018).
  • 4.Takeishi, N., Kawahara, Y., and Yairi, T.:
    "Learning Koopman invariant subspaces for dynamic mode decomposition"
    Advances in Neural Information Processing Systems 30, pp.1130-1140 (2017).
  • 5.Wang, H., Kawahara, Y., Weng, C., and Yuan, J.:
    "Representative selection with structured sparsity"
    Pattern Recognition, Vol.63, pp.268-278 (2017).
  • 6.Kawahara, Y.:
    "Dynamic mode decomposition with reproducing kernels for Koopman spectral analysis"
    Advances in Neural Information Processing Systems 29, pp.911-919 (2016).
  • 7.Xin, B., Kawahara, Y., Wang, Y., Hu, L., and Gao, W.:
    "Efficient generalized fused Lasso and its applications"
    ACM Transactions on Intelligent Systems and Technology (TIST), Vol.7, No.4, pp.60:1-60:22 (2016).
  • 8.Kawahara, Y., and Sugiyama, M.:
    "Sequential change-point detection based on direct density-ratio estimation"
    Statistical Analysis and Data Mining, Vol.5, No.2, pp.114-127 (2012).
  • 9.Kawahara, Y., Nagano, K., Tsuda, K., and Bilmes, J.A.:
    "Submodularity cuts and applications"
    Advances in Neural Information Processing Systems 22, pp.916-924 (2009).
  • 10.Kawahara, Y., Yairi, T., and Machida, K.:
    "Change-point detection in time-series data based on subspace identification"
    Proceedings of the 7th IEEE International Conference on Data Mining (ICDM’07), pp.559-564 (2007).

Related Links

Lab Members

Principal investigator

Yoshinobu Kawahara
Team Leader

Core members

Matthias Weissenbacher
Postdoctoral Researcher
Daisuke Hatano
Postdoctoral Researcher
Yoshiteru Nishimura
Technical Staff I
Keisuke Fujii
Visiting Scientist
Shunji Umetani
Visiting Scientist
Naoya Takeishi
Visiting Scientist
Takuya Konishi
Visiting Scientist

Contact Information

744 Motooka, Nishi-ku, Fukuoka-shi, Fukuoka 819-0395 Japan
Email: yoshinobu.kawahara [at] riken.jp