Cluster Kernels for Semi-Supervised Learning

NIPS 2002: Proceedings of the 15th International Conference on Neural Information Processing Systems

Volumn , Issue , 2002, Pages 585-592

  Chapelle, Olivier ^a   Weston, Jason ^a   Schölkopf, Bernhard ^a  

^a MAX PLANCK INSTITUTE FOR BIOLOGICAL CYBERNETICS   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

EIGENSPECTRUM; KERNEL CLASSIFIERS; KERNEL MATRICES; SEMI-SUPERVISED LEARNING; TWO-POINT; UNLABELED DATA;

SUPERVISED LEARNING;

EID: 32844455952     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (13)

1. A. Blum and T. Mitchell. Combining labeled and unlabeled data with co-training. In COLT: Proceedings of the Workshop on Computational Learning Theory. Morgan Kaufmann Publishers, 1998.
2. O. Chapelle, V. Vapnik, O. Bousquet, and S. Mukherjee. Choosing multiple parameters for support vector machines. Machine Learning, 46(1-3):131-159, 2002.
3. T. Jaakkola and D. Haussler. Exploiting generative models in discriminative classifiers. In Advances in Neural Information Processing, volume 11, pages 487-493. The MIT Press, 1998.
4. T. Joachims. Transductive inference for text classification using support vector machines. In Proceedings of the 16th International Conference on Machine Learning, pages 200-209. Morgan Kaufmann, San Francisco, CA, 1999.
5. A. Y. Ng, M. I. Jordan, and Y. Weiss. On spectral clustering: Analysis and an algorithm. In Advances in Neural Information Processing Systems, volume 14, 200l.
6. K Nigam, A. K McCallum, S. Thrun, and T. M. Mitchell. Learning to classify text from labeled and unlabeled documents. In Proceedings of AAAI-9S, 15th Conference of the American Association for Artificial Intelligence, pages 792-799, Madison, US, 1998. AAAI Press, Menlo Park, US.
7. B. Scholkopf, J. Shawe-Taylor, A. J. Smola, and R. C. Williamson. Generalization bounds via eigenvalues of the Gram matrix. Technical Report 99-035, NeuroColt, 1999.
8. B. Scholkopf, A. Smola, and K-R. Muller. Nonlinear component analysis as a kernel eigenvalue problem. Neural Computation, 10:1299-1310, 1998.
9. M. Seeger. Covariance kernels from Bayesian generative models. In Advances in Neural Information Processing Systems, volume 14, 200l.
10. M. Seeger. Learning with labeled and unlabeled data. Technical report, Edinburgh University, 200l.
11. M. Szummer and T. Jaakkola. Partially labeled classification with markov random walks. In Advances in Neural Information Processing Systems, volume 14, 200l.
12. K Tsuda, T. Kin, and K Asai. Marginalized kernels for biological sequences. Bioinformatics, 2002. To appear. Also presented at ICMB 2002.
13. Y. Weiss. Segmentation using eigenvectors: A unifying view. In International Conference on Computer Vision, pages 975-982, 1999.