Symbols - Introduction to Semi-Supervised Learning

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102 BIBLIOGRAPHY

[88] Thorsten Joachims. Making large-scale svm learning practical. In B. Schölkopf, C. Burges,

and A. Smola, editors, Advances in Kernel Methods - Support Vector Learning . MIT Press, 1999.

[89] Thorsten Joachims. Transductive inference for text classification using support vector ma-

chines. In Proc. 16th International Conf. on Machine Learning , pages 200-209. Morgan Kauf-

mann, San Francisco, CA, 1999.

[90] Thorsten Joachims. Transductive learning via spectral graph partitioning. In Proceedings of

ICML-03, 20th International Conference on Machine Learning , 2003.

[91] Rie Johnson and Tong Zhang. On the effectiveness of laplacian normalization for graph

semi-supervised learning. Journal of Machine Learning Research , 8( Jul):1489-1517, 2007.

[92] Rie Johnson and Tong Zhang. Two-view feature generation model for semi-supervised

learning. In The 24th International Conference on Machine Learning , 2007.

[93] Rosie Jones. Learning to extract entities from labeled and unlabeled text. Technical Report

CMU-LTI-05-191, Carnegie Mellon University, 2005. Doctoral Dissertation.

[94] Matti Kaariainen. Generalization error bounds using unlabeled data. In COLT 2005 , 2005.

[95] Ashish Kapoor, Yuan Qi, Hyungil Ahn, and Rosalind Picard. Hyperparameter and kernel

learning for graph based semi-supervised classification. In Advances in NIPS , 2005.

[96] M. Karlen, J. Weston, A. Erkan, and R. Collobert. Large scale manifold transduction. In

Andrew McCallum and Sam Roweis, editors, Proceedings of the 25th Annual International

Conference on Machine Learning (ICML 2008) , pages 448-455. Omnipress, 2008.

[97] Michael J. Kearns and Umesh V. Vazirani. An Introduction to Computational Learning Theory .

MIT Press, 1994.

[98] C. Kemp, T.L. Griffiths, S. Stromsten, and J.B. Tenenbaum. Semi-supervised learning with

trees. In Advances in Neural Information Processing System 16 , 2003.

[99] Dan

Klein.

Lagrange

multipliers

without

permanent

scarring,

2004.

http://www.cs.berkeley.edu/

∼

klein/papers/lagrange-multipliers.pdf.

[100] B. J. Knowlton and L. R. Squire.

The learning of categories: Parallel brain sys-

tems

for

item

memory

and