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RIKEN Center for Advanced Intelligence Project High-Dimensional Statistical Modeling Team

Team Leader: Makoto Yamada (Ph.D.)

Research Summary

Makoto  Yamada(Ph.D.)

We are focusing on developing machine learning algorithm for large p and small n problems such as biomarker discovery and toxicogenomics prediction. In particular, we are interested in nonlinear feature selection algorithms for such high-dimensional data, and proposing simple yet efficient algorithms. Ultimately, we want to build a machine learning framework to automatically find an important information from data.

Main Research Fields

  • Computer Science

Research Subjects

  • High-dimensional Feature Selection
  • Transfer Learning

Selected Publications

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

  • 1.Yamada, M., Lian, W, Goyal, Amit, Chen, J. Wimalawarne, K., Khan, S. A., Kaski, S., Mamitsuka, H., Chang, Y.:
    "Convex Facotrization Machine for Toxicogenomics Prediction"
    In Proceedings of the 23rd SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2017).
  • 2.Yamada, M., Takeuchi, K., Iwata, T., Taylor, J-S, & Kaski, S.:
    "Localized Lasso for High-Dimensional Regression"
    In Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS2017).
  • 3.*Iwata, T. & Yamada, M.:
    "Multi-view Anomaly Detection via Robust Probabilistic Latent Variable Models"
    In Proceedings of the Advances in Neural Information Processing Systems (NIPS 2016).
  • 4.*Wang, Y., Yin, D., Luo, J., Wang, P., Yamada, M., Chang, Y., & Mei, Q.:
    "Beyond Ranking: Optimizing Whole-Page Presentation"
    In Proceedings of the 9th ACM Conference on Web Search and Data Mining (WSDM 2016). Best paper award.
  • 5.*Gunasekar, S., Yamada, M., Yin, D., & Chang, Y.:
    "Consistent Collective Matrix Completion under Joint Low Rank Structure"
    In Proceedings of International Conference on Artificial Intelligence and Statistics (AISTATS2015).
  • 6.*Yamada, M., Sigal, L., Raptis, M., Toyoda, M., Chang, Y., & Sugiyama, M.:
    "Cross-Domain Matching with Squared-Loss Mutual Information"
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol.37, no.9, pp.1764-1776, (2015).
  • 7.*Yamada, M., Chang, Y., & Sigal, L.:
    "Domain Adaptation for Structured Regression"
    International Journal of Computer Vision (IJCV), vol. 109, Issue 1-2, pp. 126-145.
  • 8.*Yamada, M., Sigal, L., & Raptis, M.:
    "Covariate Shift Adaptation for Discriminative 3D Pose Estimation"
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol.36, pp: 235-247, (2014).
  • 9.*Yamada, M., Jitkrittum, W., Sigal, L., Xing, E. P. & Sugiyama, M.:
    "High-Dimensional Feature Selection by Feature-Wise Non-Linear Lasso"
    Neural Computation, vol.26, no.1, pp.185-207, (2014).
  • 10.*Yamada, M., Suzuki, T., Kanamori, T., Hachiya, H., & Sugiyama, M.:
    "Relative Density-Ratio Estimation for Robust Distribution Comparison"
    Advances in Neural Information Processing Systems (NIPS2011).

Related Links

Lab Members

Principal investigator

Makoto Yamada
Team Leader

Core members

Tam Thanh Le
Research Scientist
Hector Climente Gonzalez
Special Postdoctoral Researcher
Dinesh Singh
Postdoctoral Researcher
Peter Jack Naylor
Postdoctoral Researcher
Shigeyuki Matsui
Senior Visiting Scientist
Kenji Fukumizu
Senior Visiting Scientist
Hisashi Kashima
Visiting Scientist
Heewon Park
Visiting Scientist
Yuta Itoh
Visiting Scientist
Masaaki Imaizumi
Visiting Scientist
Taichiro Endo
Visiting Scientist
Benjamin Michel Claude Poignard
Visiting Scientist
Hidetoshi Shimodaira
Visiting Scientist
Akifumi Okuno
Visiting Scientist
Junya Honda
Visiting Scientist
Yoshikazu Terada
Visiting Scientist
Sho Yokoi
Visiting Scientist
Kenta Kihara
Research Part-time Worker I
Runsen Li
Research Part-time Worker I

Contact Information

Nihonbashi 1-chome Mitsui Building, 15th floor,
1-4-1 Nihonbashi,
Chuo-ku, Tokyo
103-0027, Japan

Email: makoto.yamada [at] riken.jp