Dimensionality Reduction for Semi-supervised Face Recognition

Author:

Du Weiwei,Inoue Kohei,Urahama Kiichi

Publisher

Springer Berlin Heidelberg

Reference8 articles.

1. Seeger, M.: Learning with labeled and unlabeled data. Tech. Reports, Edinburgh Univ (2001)

2. Zhu, X., Ghahramani, Z., Lafferty, J.: Semi-supervised learning using Gaussian fields and harmonic functions. In: Proc. ICML-2003, pp. 912–919 (2003)

3. Zhou, D., Bousquet, O., Lal, T.N., Weston, J., Scholkopf, B.: Learning with local and global consistency. In: Proc. NIPS 2003(2003)

4. Ng, A.Y., Jordan, M.I., Weiss, Y.: On spectral clustering: Analysis and an algorithm. In: Proc. NIPS 2001, pp. 849–856 (2001)

5. Belkin, M., Niyogi, P.: Laplacian eigenmaps for dimensionality reduction and data representation. Neural Comp. 15, 1373–1396 (2003)

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1. Semi-supervised learning with local and global consistency;International Journal of Computer Mathematics;2013-09-25

2. A Modified Semi-Supervised Learning Algorithm on Laplacian Eigenmaps;Neural Processing Letters;2010-07-20

3. Semi-supervised Learning by Spectral Mapping with Label Information;Artificial Intelligence and Computational Intelligence;2010

4. Facial Recognition;Encyclopedia of Data Warehousing and Mining, Second Edition;2009

5. A unified framework for semi-supervised dimensionality reduction;Pattern Recognition;2008-09

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