Presentation 2019-03-14
A study on the probabilistic information processing using a machine learning result
Shun Kataoka,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) We consider a framework of the probabilistic information processing utilizing the machine learning result. In probabilistic information processing, probabilistic models are usually designed by using some parameters and values of these parameters are determined so as to express the observed signal. In this study, we propose a new parameter estimation method based on EM algorithm and machine learning result. Because the purpose of the machine learning is to find parameters that express the properties of the signals of the world, we expect that the parameters expressing the observed signal can be effectively obtained by utilizing the machine learning result. We numerically verified our method by using the artificial data
Keyword(in Japanese) (See Japanese page)
Keyword(in English) probabilistic information processing / maximum likelihood estimation / EM algorithm / statical machine learning
Paper # MSS2018-89
Date of Issue 2019-03-07 (MSS)

Conference Information
Committee NLP / MSS
Conference Date 2019/3/14(2days)
Place (in Japanese) (See Japanese page)
Place (in English) Bunkyo Camp., Univ. of Fukui
Topics (in Japanese) (See Japanese page)
Topics (in English) SICE-DES, IEICE-MSS, IEICE-NLP, Work In Progress, and etc.
Chair Norikazu Takahashi(Okayama Univ.) / Morikazu Nakamura(Univ. of Ryukyus)
Vice Chair Hiroaki Kurokawa(Tokyo Univ. of Tech.) / Shigemasa Takai(Osaka Univ.)
Secretary Hiroaki Kurokawa(Hiroshima Inst. of Tech.) / Shigemasa Takai(Nippon Inst. of Tech.)
Assistant Masayuki Kimura(Kyoto Univ.) / Yutaka Shimada(Saitama Univ.) / Hideki Kinjo(Okinawa Univ.)

Paper Information
Registration To Technical Committee on Nonlinear Problems / Technical Committee on Mathematical Systems Science and its applications
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A study on the probabilistic information processing using a machine learning result
Sub Title (in English)
Keyword(1) probabilistic information processing
Keyword(2) maximum likelihood estimation
Keyword(3) EM algorithm
Keyword(4) statical machine learning
1st Author's Name Shun Kataoka
1st Author's Affiliation Otaru University of Commerce(OUC)
Date 2019-03-14
Paper # MSS2018-89
Volume (vol) vol.118
Number (no) MSS-499
Page pp.pp.45-50(MSS),
#Pages 6
Date of Issue 2019-03-07 (MSS)