Error-correcting semi-supervised learning with mode-filter on graphs

Weiwei Du, Kiichi Urahama

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

1 引用 (Scopus)

抜粋

We present a semi-supervised learning algorithm robust to label errors in training data. Our method employs the mode filter used for smoothing noisy images. We extend it from images to functions on graphs for regression of classification functions on an undirected graph. Our contribution in this paper lies in the introduction of nonlinearity in the regression in contrast to linear interpolation used in previous graph-based semi-supervised learning algorithms. Error-correcting effect of mode filters is demonstrated and the classification rates of the present learning method is evaluated with experiments for the UCI benchmark datasets contaminated with label errors.

元の言語英語
ホスト出版物のタイトル2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009
ページ2095-2100
ページ数6
DOI
出版物ステータス出版済み - 12 1 2009
イベント2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009 - Kyoto, 日本
継続期間: 9 27 200910 4 2009

出版物シリーズ

名前2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009

その他

その他2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009
日本
Kyoto
期間9/27/0910/4/09

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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  • これを引用

    Du, W., & Urahama, K. (2009). Error-correcting semi-supervised learning with mode-filter on graphs. : 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009 (pp. 2095-2100). [5457539] (2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009). https://doi.org/10.1109/ICCVW.2009.5457539