Prediction on a graph with a perceptron

Advances in Neural Information Processing Systems

Volumn , Issue , 2007, Pages 577-584

  Herbster, Mark ^a   Pontil, Massimiliano ^a  

^a UNIVERSITY COLLEGE LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

CUT SIZE; FINITE SET; GRAPH DIAMETER; LOSS BOUNDS; MISTAKE BOUNDS; NATURAL PROPERTIES; NEAREST NEIGHBORS; ONLINE PREDICTION; PERCEPTRON; PERCEPTRON LEARNING; SMALL PERTURBATIONS; UPPER BOUND;

SET THEORY;

FORECASTING;

EID: 43249123791     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (13)

1. C. Gentile. The robustness of the p-norm algorithms. Machine Learning, 53(3):265-299, 2003.
2. A. Blum and S. Chawla. Learning from labeled and unlabeled data using graph mincuts. In ICML 2002, pages 19-26. Morgan Kaufmann, San Francisco, CA, 2002.
3. R. I. Kondor and J. Lafferty. Diffusion kernels on graphs and other discrete input spaces. In ICML 2002, pages 315-322. Morgan Kaufmann, San Francisco, CA, 2002.
4. X. Zhu, Z. Ghahramani, and J. Lafferty. Semi-supervised learning using gaussian fields and harmonic functions. In ICML 2003, pages 912-919, 2003.
5. A. Smola and R.I. Kondor. Kernels and regularization on graphs. In COLT 2003, pages 144-158, 2003.
6. M. Belkin, I. Matveeva, and P. Niyogi. Regularization and semi-supervised learning on large graphs. In COLT 2004, pages 624 - 638, Banff, Alberta, 2004. Springer.
7. T. Zhang and R. Ando. Analysis of spectral kernel design based semi-supervised learning. In Y. Weiss, B. Schölkopf, and J. Platt, editors, NIPS 18, pages 1601-1608. MIT Press, Cambridge, MA, 2006.
8. M. Herbster, M. Pontil, and L.Wainer. Online learning over graphs. In ICML 2005, pages 305-312, New York, NY, USA, 2005. ACM Press.
9. Y. Freund and R. E. Schapire. Large margin classification using the perceptron algorithm. Machine Learning, 37(3):277-296, 1999.
10. D. Klein and M. Randić. Resistance distance. Journal of Mathematical Chemistry, 12(1):81-95, 1993.
11. J. M. Barzdin and R. V. Frievald. On the prediction of general recursive functions. Soviet Math. Doklady, 13:1224-1228, 1972.
12. N. Aronszajn. Theory of reproducing kernels. Trans. Amer. Math. Soc., 68:337-404, 1950.
13. D. Karger and C. Stein. A new approach to the minimum cut problem. JACM, 43(4):601-640, 1996.