論文

査読有り
2010年

Direct density ratio estimation with dimensionality reduction

Proceedings of the 10th SIAM International Conference on Data Mining, SDM 2010
  • Masashi Sugiyama
  • ,
  • Satoshi Hara
  • ,
  • Paul Von Bünau
  • ,
  • Taiji Suzuki
  • ,
  • Takafumi Kanamori
  • ,
  • Motoaki Kawanabe

開始ページ
595
終了ページ
606
記述言語
掲載種別
研究論文(国際会議プロシーディングス)
DOI
10.1137/1.9781611972801.52
出版者・発行元
SIAM

Methods for directly estimating the ratio of two probability density functions without going through density estimation have been actively explored recently since they can be used for various data processing tasks such as non-stationarity adaptation, outlier detection, conditional density estimation, feature selection, and independent component analysis. However, even the state-of-the-art density ratio estimation methods still perform rather poorly in high-dimensional problems. In this paper, we propose a new density ratio estimation method which incorporates dimensionality reduction into a density ratio estimation procedure. Our key idea is to identify a low-dimensional subspace in which the two densities corresponding to the denominator and the numerator in the density ratio are significantly different. Then the density ratio is estimated only within this low-dimensional subspace. Through numerical examples, we illustrate the effectiveness of the proposed method. Copyright © by SIAM.

リンク情報
DOI
https://doi.org/10.1137/1.9781611972801.52
Scopus
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84880131045&origin=inward
Scopus Citedby
https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=84880131045&origin=inward
URL
http://dblp.uni-trier.de/db/conf/sdm/sdm2010.html#conf/sdm/SugiyamaHBSKK10
ID情報
  • DOI : 10.1137/1.9781611972801.52
  • DBLP ID : conf/sdm/SugiyamaHBSKK10
  • SCOPUS ID : 84880131045

エクスポート
BibTeX RIS