Leveraged vector machines

Advances in Neural Information Processing Systems

Volumn , Issue , 2000, Pages 610-616

  Singer, Yoram ^a  

^a HEBREW UNIVERSITY OF JERUSALEM   (Israel)

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTIVE BOOSTING; SUPPORT VECTOR MACHINES;

CLASSIFICATION TASKS; DIFFERENTIAL FUNCTIONS; EXPONENTIAL LOSS FUNCTION; GENERALIZED ADDITIVE MODEL; ITERATIVE ALGORITHM; LOSS FUNCTIONS; RUNNING TIME; VECTOR MACHINES;

ALGORITHMS;

EID: 0006413386     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (13)

1. Corinna Cortes and Vladimir Vapnik. Support-vector networks. Machine Learning, 20(3):273-297, September 1995.
2. N. Duffy and D. Helmbold. A geometric approach to leveraging weak learners. EuroCOLT '99.
3. Yoav Freund. Boosting a weak learning algorithm by majority. Information and Computation, 121(2):256-285, 1995.
4. Yoav Freund and Robert E. Schapire. A decision-theoretic generalization of on-line learning and an application to boosting. Journal of Computer and System Sciences, 55(1): 119-139, August 1997.
5. J. Friedman, T. Hastie, and R. Tibshirani. Additive logistic regression: a statistical view of boosting. Tech. Report, 1998.
6. Michael Kearns and Leslie G. Valiant. Cryptographic limitations on learning Boolean formulae and finite automata Journal of the Association for Computing Machinery, 41(l):67-95, January 1994.
7. John D. Lafferty. Additive models, boosting and inference for generalized divergences. In Proceedings of the Twelfth Annual Conference on Computational Learning Theory, 1999.
8. L. Mason, J. Baxter, P. Bartlett, and M. Frean. Doom II. Technical report, Depa. of Sys. Eng. ANU 1999.
9. G. Rätsch, T.Onoda, and K.-R. Müller. Regularizing adaboost. In Advances in Neural Info. Processing Systems 12,1998.
10. Robert E. Schapire. The strength of weak learnability. Machine Learning, 5(2):197'-227, 1990.
11. Robert E. Schapire and Yoram Singer. Improved boosting algorithms using confidence-rated predictions. COLT'98.
12. V. N. Vapnik. Estimation of Dependences Based on Empirical Data. Springer-Verlag, 1982.
13. Vladimir N. Vapnik. The Nature of Statistical Learning Theory. Springer, 1995.