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J-GLOBAL ID：201302218270354769   Reference number：13A0961702

Change-point detection in time-series data by relative density-ratio estimation

相対的密度比推定による時系列データの中での変化点の検出

Author (5)： LIU Song (Tokyo Inst. of Technol., 2-12-1 O-okayama, Meguro-ku, Tokyo 152-8552, JPN) ,  YAMADA Makoto (NTT Communication Sci. Laboratories, 2-4, Hikaridai, Seika-cho, Kyoto 619-0237, JPN) ,  COLLIER Nigel (National Inst. of Informatics (NII), 2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo 101-8430, JPN) ,  COLLIER Nigel (European Bioinformatics Inst. (EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, GBR) ,  SUGIYAMA Masashi (Tokyo Inst. of Technol., 2-12-1 O-okayama, Meguro-ku, Tokyo 152-8552, JPN)
Material： Neural Networks  (Neural Netw)
Volume： 43  Page： 72-83  Publication year： Jul. 2013 
JST Material Number： T0698A  ISSN： 0893-6080  Document type： Article
Article type： 原著論文  Country of issue： United Kingdom (GBR)  Language： ENGLISH (EN)

Thesaurus term： *statistical estimation ,  *time series analysis ,  detection ,  divergence ,  evaluation test ,  speech analysis ,  system evaluation ,  time series ,  time course ,  Web (information system) ,  accuracy ,  change point detection
Semi thesaurus term： Pearson発散 ,  ツィッター ,  *密度比推定 ,  twitter

JST classification (2)： System and control theory in general  (IA02010H) ,  Numerical computation  (JE02000J)

Reference (54)：

• Adams, R. P., & MacKay, D. J. C. (2007). Bayesian online changepoint detection. Technical Report. arXiv:0710.3742v1 [stat.ML].
• Ali, S. M., & Silvey, S. D. (1966). A general class of coefficients of divergence of one distribution from another. Journal of the Royal Statistical Society, Series B, 28(1), 131-142.
• Basseville, M., & Nikiforov, I. V. (1993). Detection of abrupt changes: theory and application. Upper Saddle River, NJ, USA: Prentice-Hall, Inc.
• Bellman, R. (1961). Adaptive control processes: a guided tour. Princeton, NJ, USA: Princeton University Press.
• Bickel, S., Br?ckner, M., & Scheffer, T. (2007). Discriminative learning for differing training and test distributions. In Proceedings of the 24th international conference on machine learning (pp. 81-88).

Terms in the title (3)： 相対的密度 ,  推定 ,  時系列データ