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SUMIO WATANABE  Researcher Information
  
  
  
    
      
    
    
      | Family Name | 
      渡邊  | 
      WATANABE  | 
     
    
      | First Name | 
      澄夫  | 
      SUMIO  | 
     
    
      | Organization | 
      
Tokyo Institute of Technology
(formerly TokyoTech)School of Computing
 
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      | Title | 
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      | ResearcherID | 
      C-3880-2015 
       
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      | ORCID ID | 
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      Area of Supervision   : Primary | 
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      | Research Bases | 
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      | Specialized Field | 
      General mathematics (including Probability theory/ Statistical mathematics) (Mathematics and Information Science) Others (Mathematical Learning Theory)
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      | Researcher Profile | 
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      | Lecture Note | 
      TokyoTech Open Course Ware | 
     
    
      | Degree | 
      
      
        
神経回路網援用超音波影像法による3次元物体認識, 
        Thesis, 
        Doctor of Engineering, 
        
        1993/--/--, 
        
        
         
      
        
Spectral analysis for multipole ghost, 
        
        Master of Science, 
        
        1984/--/--, 
        
        
         
      
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      | Research Highlight | 
      
      
        
SUMIO WATANABE.
        Highly Cited Paper: A widely applicable Bayesian information criterion.
        2019-2019. 
        被引用回数上位1%論文に選ばれました。Sumio Watanabe, A widely applicable Bayesian information criterion. Journal of Ma.... 
        
       
      
        
SUMIO WATANABE.
        Highly Cited Paper: Asymptotic equivalence of Bayes Cross Validation and WAIC.
        2017-. 
        被引用回数上位1%論文に選ばれました。Sumio Watanabe, Asymptotic Equivalence of Bayes Cross Validation and Widely Appli.... 
        
       
      
        
Masahiro Koujima,
SUMIO WATANABE.
        ICANN Best Paper Award.
        2017-2017. 
        
        
       
      
        
SUMIO WATANABE.
        Information Criteria WAIC and WBIC.
        2010-2016. 
        New Information Criteria WAIC and WBIC were devised, which are available for an arbitrary triple of .... 
        
       
      
        
SUMIO WATANABE.
        Algebraic Geometry and Learning Theory.
        2002-2017. 
        Based on algebraic geometry, new learning theory was established, which clarified statistical behavi.... 
        
       
      
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