Presentation | 2005-09-21 Fast Semi-Supervised Learning on Nearest Neighbor Graphs Weiwei DU, Kiichi URAHAMA, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | A simple label propagation technique is presented for semi-supervised learning of pattarn classifiers. In our technique, label is propagated on a sparse unweithed graph called the kNN graph. This propagation can be executed with only integer computation and stops in finite steps. Our method is therefore faster than the conventional label propagation methods dealing with real numbers and with slow convergence. We develop an unsupervised learning method exploiting this label propagation procedure and apply it to select data to be labeled in our semi-supervised learning. The performance of the present method is examined for a synthetic dataset and some real datasets. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | semi-supervised learning / label propagation / unsupervised learning / outlier detection / nearest neighbor graph |
Paper # | NLC2005-24,PRMU2005-51 |
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Committee | NLC |
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Conference Date | 2005/9/14(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Natural Language Understanding and Models of Communication (NLC) |
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Language | ENG |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Fast Semi-Supervised Learning on Nearest Neighbor Graphs |
Sub Title (in English) | |
Keyword(1) | semi-supervised learning |
Keyword(2) | label propagation |
Keyword(3) | unsupervised learning |
Keyword(4) | outlier detection |
Keyword(5) | nearest neighbor graph |
1st Author's Name | Weiwei DU |
1st Author's Affiliation | Faculty of Design, Kyushu University() |
2nd Author's Name | Kiichi URAHAMA |
2nd Author's Affiliation | Faculty of Design, Kyushu University |
Date | 2005-09-21 |
Paper # | NLC2005-24,PRMU2005-51 |
Volume (vol) | vol.105 |
Number (no) | 299 |
Page | pp.pp.- |
#Pages | 6 |
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