High-Dimensional Statistical Modeling Unit (RIKEN AIP)

We are focusing on developing machine learning algorithm for science including feature selection, topological data analysis, and transfer learning. In particular, we are interested in nonlinear algorithms for high-dimensional data. Ultimately, we want to build a machine learning framework to automatically find an important information from data.


Paid intern positions are available for motivated M.S. or Ph.D. students. Please feel free to send me your resume!

Ph.D. student
We accept graduate students from Graduate School of Informatics, Kyoto University.

E-mail: textnormal{makoto.yamada@riken.jp}


2020/01/07 Two papers have been accepted to AISTATS 2020.
2019/11/11 One paper has been accepted to AAAI 2020.
2019/09/04 Three papers have been accepted to NeurIPS 2019.
2019/08/12 Our kernel based attention paper has been accepted to EMNLP-IJCNLP 2019.
2019/04/22 Tam's safe screening paper has been accepted to ICML 2019.
2019/04/10 Our nonlinear feature selection paper has been accepted to ISMB/ECCB 2019.


RIKEN Kyoto Office
Research Bldg. No.15
Kyoto University
Yoshida-honmachi, Sakyo-ku, Kyoto