Presentation 2016-11-16
Online heterogeneous mixture machine learning
Tetsuya Ikehara, Satoshi Yamane,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) In recent years, utilization of big data has attracted the attention, and many techniques about data analysis have been proposed. The real time data analysis has become important, but big data analysis is difficult because the data has a plurality of different regularity. There is algorithm of heterogeneous mixture machine learning to analyze the data efficiently. In this study, we propose algorithm of online heterogeneous mixture machine learning based on online EM algorithm.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Big Data / Online Leaning / Mixture Machine Learning
Paper # IBISML2016-54
Date of Issue 2016-11-09 (IBISML)

Conference Information
Committee IBISML
Conference Date 2016/11/16(3days)
Place (in Japanese) (See Japanese page)
Place (in English) Kyoto Univ.
Topics (in Japanese) (See Japanese page)
Topics (in English) Information-Based Induction Science Workshop (IBIS2016)
Chair Kenji Fukumizu(ISM)
Vice Chair Masashi Sugiyama(Univ. of Tokyo) / Hisashi Kashima(Kyoto Univ.)
Secretary Masashi Sugiyama(Univ. of Tokyo) / Hisashi Kashima(Nagoya Inst. of Tech.)
Assistant Toshihiro Kamishima(AIST) / Tomoharu Iwata(NTT)

Paper Information
Registration To Technical Committee on Infomation-Based Induction Sciences and Machine Learning
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Online heterogeneous mixture machine learning
Sub Title (in English)
Keyword(1) Big Data
Keyword(2) Online Leaning
Keyword(3) Mixture Machine Learning
Keyword(4)
1st Author's Name Tetsuya Ikehara
1st Author's Affiliation Kanazawa University(Kanazawa Univ.)
2nd Author's Name Satoshi Yamane
2nd Author's Affiliation Kanazawa University(Kanazawa Univ.)
Date 2016-11-16
Paper # IBISML2016-54
Volume (vol) vol.116
Number (no) IBISML-300
Page pp.pp.59-64(IBISML),
#Pages 6
Date of Issue 2016-11-09 (IBISML)