
Masashi Sugiyama (Ph.D.)
Title
Team Leader
History
2001 | Assistant Professor, Department of Computer Science, Graduate School of Information Science and Engineering, Tokyo Institute of Technology, Tokyo, Japan. |
2003 | Associate Professor, Department of Computer Science, Graduate School of Information Science and Engineering, Tokyo Institute of Technology, Tokyo, Japan. |
2014 | Professor, Department of Complexity Science and Engineering, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan. (Present) |
2016 | Director, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan. (Present) |
Members
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Research scientistGang Niu
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Research scientistFumiko Kawasaki
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Postdoctoral researcherJingfeng Zhang
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Postdoctoral researcherJiaqi Lyu
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Postdoctoral researcherShuo Chen
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Senior visiting scientistShinichi Nakajima
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Visiting scientistYoshihiro Nagano
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Visiting scientistFlorian Yger
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Visiting scientistTakashi Ishida
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Visiting scientistMiao Xu
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Visiting scientistTakayuki Osa
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Visiting scientistBo Han
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Visiting scientistYuko Kuroki
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Visiting scientistFeng Liu
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Visiting scientistLei Feng
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Visiting scientistTongliang Liu
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Part-time worker IMasahiro Fujisawa
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Part-time worker IYifan Zhang
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
Theoretical analysis of machine learning algorithms
Real-world application of machine learning algorithms
RIKEN Website URL
Poster(s)
- FY2019 Research Results(PDF 646KB) (Japanese version)
- FY2018 Research Results(PDF 1.41MB)
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