Paper Info

Title | ||
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Semi-supervised orthogonal discriminant analysis via label propagation |

Abstract | ||
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Trace ratio is a natural criterion in discriminant analysis as it directly connects to the Euclidean distances between training data points. This criterion is re-analyzed in this paper and a fast algorithm is developed to find the global optimum for the orthogonal constrained trace ratio problem. Based on this problem, we propose a novel semi-supervised orthogonal discriminant analysis via label propagation. Differing from the existing semi-supervised dimensionality reduction algorithms, our algorithm propagates the label information from the labeled data to the unlabeled data through a specially designed label propagation, and thus the distribution of the unlabeled data can be explored more effectively to learn a better subspace. Extensive experiments on toy examples and real-world applications verify the effectiveness of our algorithm, and demonstrate much improvement over the state-of-the-art algorithms. |

Year | DOI | Venue |
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2009 | 10.1016/j.patcog.2009.04.001 | Pattern Recognition |

Keywords | Field | DocType |

semi-supervised orthogonal discriminant analysis,discriminant analysis,label propagation,existing semi-supervised dimensionality reduction,state-of-the-art algorithm,fast algorithm,training data point,unlabeled data,label information,orthogonal discriminant analysis,natural criterion,semi supervised learning,dimensionality reduction,euclidean distance | Dimensionality reduction,Semi-supervised learning,Artificial intelligence,Euclidean geometry,Information processing,Subspace topology,Pattern recognition,Algorithm,Curse of dimensionality,Supervised learning,Linear discriminant analysis,Machine learning,Mathematics | Journal |

Volume | Issue | ISSN |

42 | 11 | Pattern Recognition |

Citations | PageRank | References |

51 | 1.87 | 28 |

Authors | ||

4 |

Authors (4 rows)

Cited by (51 rows)

References (28 rows)

Name | Order | Citations | PageRank |
---|---|---|---|

Feiping Nie | 1 | 7061 | 309.42 |

Shiming Xiang | 2 | 2136 | 110.53 |

Yangqing Jia | 3 | 7563 | 351.84 |

Changshui Zhang | 4 | 5506 | 323.40 |