Kenji Fukumizu's Home Page

The Institute of Statistical Mathematics
Professor, Department of Mathematical Analysis and Statistical Inference
Director, Research Center for Statistical Machine Learning

Professor, Department of Statistical Science, Graduate University of Advanced Studies (SOKENDAI)

10-3 Midori-cho, Tachikawa, Tokyo 190-8562 Japan
E-mail: 'fukumizu' ATT 'ism' DOTT 'ac' DOTT jp
Room: D606. Access to ISM

Workshop on Functional Inference and Machine Intelligence (FIMI 2023) March 14-16, 2023.

A kernel Stein test for comparing latent variable models,
by Heishiro Kanagawa, Wittawat Jitkrittum, Lester Mackey, Kenji Fukumizu, Arthur Gretton
Journal of the Royal Statistical Society Series B: Statistical Methodology,

Controlling Posterior Collapse by an Inverse Lipschitz Constraint on the Decoder Network
by Yuri Kinoshita, Kenta Oono, Kenji Fukumizu, Yuichi Yoshida, Shin-ichi Maeda, been accepted in ICML 2023 paper

Neural Fourier Transform: A General Approach to Equivariant Representation Learning
by Masanori Koyama, Kenji Fukumizu, Kohei Hayashi, Takeru Miyato arXiv

Unsupervised Learning of Equivariant Structure from Sequences
by Takeru Miyato, Masanori Koyama, Kenji Fukumizu, NeurIPS 2012 paper




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My research Interest:
I am interested in thoery and practice of learning with complex and structured data, and working from the viewpoints of statistics, mathematics and machine learning. More specific research projects include the following topics;

• Deep Learning: Mathematical methods in deep learning, such as equivariance, transfer learning, generalization, and so on
• Topological Data Analysis (TDA): A new methodoogy of data anlalysis for complex geometrical objects. TDA uses persistence homology, which expresses topological and geometrical information of data in an algebraic form.
• Kernel method: Nonparametric data analysis with positive definite kernels and reproducing kernel Hilbert spaces.

Welcome! I welcome students and collaborators interested in the above topics. Contact me by email.


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Publications


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Softwares


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Selected talks


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Courses

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Curriculum Vitae


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Lab Members


• Hideto Nakashima (Project Assistant Professor)
• Shoji Toyota (Project Researcher, ISM)
• Yuto Tanimoto (Ph.D. Candidate)Aichi Steel Corporation
• Eiki Shimizu (Ph.D. Candidate)
• Kyoko Akatsuka, Shioko Fukuda (Secretary)

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Alumni


• Hironori Murase (Aichi Steel Corporation)
• Penzhou Wu (TU Berlin)
• Yoh-ichi Mototake (Associate Professor, Hitotsubashi University)
• Masaaki Imaizumi (Associate Professor, University of Tokyo)
• Jin Zhou (Former Project Researcher)
• Yuki Saito (ZOZO Research)
• Daniel Andrade (Hiroshima University)
• Song Liu (University of Bristol, Lecturer)
• Motonobu Kanagawa (EURECOM, France)
• Yoshimasa Uematsu (Associate Professor, Hitotsubashi University)
• Takashi Arai (Shiga University, Assistant Professor)
• Momoko Hayamizu (Waseda University, Associate Professor)
• Shaogao Lv (Visiting Associate Professor, Southwestern University of Finance and Economic)
• Yusuke Aikawa (Master Degree, Tokyo Institute of Technology)
• Yu NIshiyama(Associate Professor, The University of Electro-Communications)
• Md Ashad Alam (Tulane University)
• Jonathan Root (NSF Summer Program, June - August 2013, Boston Univ.)
• Revant Kumar (student intern, May 2013 - July 2013, IIT Guwahati.)
• Pierre Chiche (visiting student in 2012 from J.-P. Vert's lab.,Mines ParisTech.)
• Masamichi Sato (Dai Nippon Printing Co., Ltd.)
• Francesco Dinuzzo (Univ. Pavia, visitor till March 2011) (Meta)
• Yusuke Watanabe (Amazon)
• Yuichi Shiraishi (National Cancer Center)
• Tomoko Ikeda-Fukazawa (Meiji University, Professor)
• Marco Cuturi (Apple, CREST - ENSAE, Universite Paris-Saclay, Professor)

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Academic Services


• Editorial services:
  • Former Chief Editor, Annals of the Institute of Statistical Mathematics (Springer)
  • Action Editor, Journal of Machine Learning Research. (MIT Press)
  • Editor, Foundations and Trends in Machine Learning. (Now Publishers)

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