Centers & Labs

RIKEN Center for Advanced Intelligence Project

Structured Learning Team

Team Leader: Yoshinobu Kawahara (D.Eng.)
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 Field

Computer Science

Related Research Fields

Physics / Engineering

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. 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) (in press)
  2. Wang, H., Kawahara, Y., Weng, C., and Yuan, J.:
    "Representative selection with structured sparsity"
    Pattern Recognition, Vol.63, pp.268-278 (2017).
  3. Kawahara, Y.:
    "Dynamic mode decomposition with reproducing kernels for Koopman spectral analysis"
    Advances in Neural Information Processing Systems 29, pp.911-919 (2016).
  4. *Kawahara, Y., Iyer, R., and Bilmes, J.:
    "On approximate non-submodular minimization via tree-structured supermodularity"
    Proceedings of the 18th International Conference on Artificial Intelligence and Statistics (AISTATS’15), pp.444-452 (2015).
  5. *Xin, B., Kawahara, Y., Wang, Y., and Gao, W.:
    "Efficient generalized fused Lasso with application to the diagnosis of Alzheimer’s disease"
    Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI’14), pp.2163-2169 (2014).
  6. *Nagano, K., and Kawahara, Y.:
    "Structured convex optimization under submodular constraints"
    Proceedings of the 29th Annual Conference on Uncertainty in Artificial Intelligence (UAI’13), pp.459-468 (2013).
  7. *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).
  8. *Kawahara, Y., and Washio, T.:
    "Prismatic algorithm for discrete D.C. programming problem"
    Advances in Neural Information Processing Systems 24, pp.2106-2114 (2011).
  9. *Kawahara, Y., Nagano, K., Tsuda, K., and Bilmes, J.:
    "Submodularity cuts and applications"
    Advances in Neural Information Processing Systems 22, pp.916-924 (2009).

Contact information

6-2-3 Furuedai,
Osaka 565-0874 Japan

Email: yoshinobu.kawahara [at]

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