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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.

Main Research Fields

  • Computer Science

Related Research Fields

  • Physics
  • Engineering
  • Mathematics

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

Selected Publications

Papers with an asterisk(*) are based on research conducted outside of RIKEN.

  • 1.Fujii, K., Kawasaki, T., Inaba, Y., and Kawahara, Y.:
    "Prediction and classification in equation-free collective motion dynamics"
    PLOS Computational Biology, Vol.14, No.11, e1006545 (2018).
  • 2.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).
  • 3.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).
  • 4.Takeishi, N., Kawahara, Y., Tabei, Y., and Yairi, T.:
    "Bayesian dynamic mode decomposition"
    Proceedings of the 26th International Conference on Joint Conference on Artificial Intelligence (IJCAI'17), pp.2814-2821 (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 Trans. 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., and Washio, T.:
    "Prismatic algorithm for discrete D.C. programming problem"
    Advances in Neural Information Processing Systems 24, pp.2106-2114 (2011).
  • 10.*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).

Related Links

Lab Members

Principal investigator

Yoshinobu Kawahara
Team Leader

Core members

Israr Ul Haq
Postdoctoral Researcher
Naoya Takeishi
Postdoctoral Researcher
Yoshiteru Nishimura
Technical Staff I

Contact Information

6-2-3 Furuedai,
Osaka 565-0874 Japan
Email: yoshinobu.kawahara [at] riken.jp