Mahalanobis-based adaptive nonlinear dimension reduction

Djamila Aouada, Yuliy Baryshnikov, Hamid Krim

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

1 被引用数 (Scopus)

抄録

We define a new adaptive embedding approach for data dimension reduction applications. Our technique entails a local learning of the manifold of the initial data, with the objective of defining local distance metrics that take into account the different correlations between the data points. We choose to illustrate the properties of our work on the isomap algorithm. We show through multiple simulations that the new adaptive version of isomap is more robust to noise than the original non-adaptive one.

本文言語英語
ホスト出版物のタイトルProceedings - 2010 20th International Conference on Pattern Recognition, ICPR 2010
ページ742-745
ページ数4
DOI
出版ステータス出版済み - 11 18 2010
外部発表はい
イベント2010 20th International Conference on Pattern Recognition, ICPR 2010 - Istanbul, トルコ
継続期間: 8 23 20108 26 2010

出版物シリーズ

名前Proceedings - International Conference on Pattern Recognition
ISSN(印刷版)1051-4651

その他

その他2010 20th International Conference on Pattern Recognition, ICPR 2010
Countryトルコ
CityIstanbul
Period8/23/108/26/10

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

引用スタイル