Query by committee, linear separation and random walks

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 1572, Issue , 1999, Pages 34-49

  Bachrach, Ran ^a   Fine, Shai ^a   Shamir, Eli ^a  

^a HEBREW UNIVERSITY OF JERUSALEM   (Israel)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; LEARNING ALGORITHMS; RANDOM PROCESSES; SUPPORT VECTOR MACHINES;

ACTIVE LEARNING METHODS; CONVEX BODY; EXPONENTIAL TIME; LEARNING PROBLEM; LINEAR SEPARATION; LINEAR SEPARATORS; QUERY BY COMMITTEES; TIME COMPLEXITY;

MONTE CARLO METHODS;

EID: 84947767124     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-49097-3_4     Document Type: Conference Paper

References (12)

1. R. Bachrach, S. Fine, and E. Shamir. Query by committee, linear separation and random walks-full version. 1998. Available at http://www. cs. huj i. ac. il/labs/learning/Papers/HLT_list. html.
2. C. Burges. A tutorial on support vector machines for pattern recognition. 1998. Available at http://svm. research. bell-labs. com/SVMdoc. html.
3. D. Cohn, L. Atlas, and R. Ladner. Training connectionist networks with queries and selective sampling. Advanced in Neural Information Processing Systems 2, 1990.
4. M. Dyer, A. Frieze, and R. Kannan. A random polynomial time algorithm for approximating the volume of convex bodies. Journal of the Association for Computing Machinery, 38, Number 1: 1-17, 1991.
5. H. G. Eggleston. Convexity. Cambridge Univ. Press, 1958.
6. Y. Freund, H. Seung, E. Shamir, and N. Tishby. Selective sampling using the query by committee algorithm. Macine Learning, 28: 133-168, 1997.
7. L. Grotchel, L. Lovasz, and A. Schrijver. Geometric algorithms and Combinatorial Optimization. Springer-Verlag, Berlin, 1988.
8. D. Haussler, M. Kearns, and R. E. Schapie. Bounds on the sample complexity of bayesian learning using information theory and the vc dimension. Machine Learning, 14: 83-113, 1994.
9. L. Lovasz and M. Simonovits. Random walks in a convex body and an improved volume algorithm. Random Structures and Algorithms, 4, Number 4: 359-412, 1993.
10. D. A. McAllester. Some pac-bayesian theorems. Proc. of the Eleventh Annual Conference on Computational Learning Theory, pages 230-234, 1998.
11. H. S. Seung, M. Opper, and H. Sompolinsky. Query by committe. Proc. of the Fith Workshop on Computational Learning Theory, pages 287-294, 1992.
12. J. Shawe-Taylor and R. C. Williamson. A pac analysis of a bayesian estimator. Proc. of the Tenth Annual Conference on Computational Learning Theory., 1997.