Masashi Sugiyama
Masashi Sugiyama (Ph.D.)
Title
Team Leader
History
2001Assistant Professor, Department of Computer Science, Graduate School of Information Science and Engineering, Tokyo Institute of Technology, Tokyo, Japan.
2003Associate Professor, Department of Computer Science, Graduate School of Information Science and Engineering, Tokyo Institute of Technology, Tokyo, Japan.
2014Professor, Department of Complexity Science and Engineering, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan. (Present)
2016Director, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan. (Present)

Members

  • Team leader
    Masashi Sugiyama
  • Senior research scientist
    Gang Niu
  • Research scientist
    Takashi Ishida
  • Research scientist
    Shuo Chen
  • Special postdoctoral researcher
    Masahiro Fujisawa
  • Postdoctoral researcher
    Yifan Zhang
  • Postdoctoral researcher
    Zhen-yu Zhang
  • Postdoctoral researcher
    Okan Koc
  • Postdoctoral researcher
    Ming-kun Xie
  • Postdoctoral researcher
    Xinqiang Cai
  • Senior visiting scientist
    Shinichi Nakajima
  • Visiting scientist
    Futoshi Futami
  • Visiting scientist
    Florian Yger
  • Visiting scientist
    Miao Xu
  • Visiting scientist
    Takayuki Osa
  • Visiting scientist
    Bo Han
  • Visiting scientist
    Fumiko Kawasaki
  • Visiting scientist
    Takahiro Mimori
  • Visiting scientist
    Nan Lu
  • Visiting scientist
    Feng Liu
  • Visiting scientist
    Jingfeng Zhang
  • Visiting scientist
    Tongliang Liu
  • Visiting scientist
    Salah Ghamizi
  • Visiting scientist
    Tingting Zhao
  • Visiting scientist
    Peng Zhao
  • Student trainee
    Alexander Soen
  • Student trainee
    Geng Yu
  • Student trainee
    Zhiqiang Kou
  • Intern
    Jiaqi Yang
  • Junior research associate
    Yuting Tang
  • Junior research associate
    Wei Wang
  • Junior research associate
    Ryota Ushio
  • Part-time worker I
    Johannes Ackermann
  • Part-time worker I
    Jiahuan Li

Introduction

Recently, machine learning technology with big data has been actively investigated and its effectiveness has been demonstrated. However, depending on application domains, it is difficult or even it is not possible to collect a large amount of data. In the Imperfect Information Learning Team, for various machine learning tasks including supervised learning, unsupervised learning, and reinforcement learning, we develop novel algorithms that allow accurate learning from limited information. We also elucidate their theoretical properties and apply them to various real-world applications ranging from fundamental science to business.

Main Research Field
Computer Science
Research Field
Engineering / Mathematics
Research Subjects
Development of machine learning algorithms from imperfect information
Theoretical analysis of machine learning algorithms
Real-world application of machine learning algorithms
RIKEN Website URL

Poster(s)

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