Agnostic learning nonconvex function classes

Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)

Volumn 2375, Issue , 2002, Pages 1-13

  Mendelson, Shahar ^a   Williamson, Robert C ^a  

^a AUSTRALIAN NATIONAL UNIVERSITY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTERS;

AGNOSTIC LEARNING; CONDITIONAL EXPECTATION; FUNCTION CLASS; LOWER-BOUND PROOFS; NONCONVEX FUNCTIONS; NONUNIQUENESS; SAMPLE COMPLEXITY; SAMPLE COMPLEXITY BOUNDS;

ARTIFICIAL INTELLIGENCE;

EID: 84937427676     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/3-540-45435-7_1     Document Type: Conference Paper

References (17)

1. Peter L. Bartlett, Olivier Bousquet, Shahar Mendelson, "Localized Rademacher averages", in COLT2002 (these proceedings).
2. Shai Ben-David and Michael Lindenbaum, "Learning Distributions by their Density Levels - A Paradigm for Learning without a Teacher," in Computational Learning Theory - EUROCOLT'95, pages 53-68 (1995).
3. Dietrich Braess, Nonlinear Approximation Theory, Springer-Verlag, Berlin, 1986.
4. Richard M. Dudley, Uniform Central Limit Theorems, Cambridge Studies in Advanced Mathematics 63, Cambridge University Press 1999.
5. David Haussler, "Decision Theoretic Generalizations of the PAC Model for Neural Net and Other Learning Applications," Information and Computation, 100, 78-150 (1992).
6. Michael J. Kearns, Robert E. Schapire and Linda M. Sellie, "Toward Efficient Agnostic Learning," pages 341-352 in Proceedings of the 5th Annual Workshop on Computational Learning Theory, ACM press, New York, 1992.
7. Wee Sun Lee, Agnostic Learning and Single Hidden Layer Neural Networks, Ph.D. Thesis, Australian National University, 1996.
8. Wee Sun Lee, Peter L. Bartlett and Robert C. Williamson, "Efficient Agnostic Learning of Neural Networks with Bounded Fan-in," IEEE Trans. on Information Theory, 42(6), 2118-2132 (1996).
9. Wee Sun Lee, Peter L. Bartlett and Robert C. Williamson, "The Importance of Convexity in Learning with Squared Loss" IEEE Transactions on Information Theory 44(5), 1974-1980, 1998 (earlier version in Proceedings of the 9th Annual Conference on Computational Learning Theory, pages 140-146, 1996.)
10. Shahar Mendelson, "Improving the sample complexity using global data," IEEE transactions on Information Theory, to appear. http://axiom.anu.edu.au/~shahar
11. Shahar Mendelson "Rademacher averages and phase transitions in Glivenko-Cantelli classes" IEEE transactions on Information Theory, 48(1), 251-263, (2002).
12. Shahar Mendelson "A few remarks on Statistical Learning Theory", preprint. http://axiom.anu.edu.au/-shahar
13. S. B. Stechkin, "Approximation Properties of Sets in Normed Linear Spaces," Revue de mathematiques pures et appliquees, 8, 5-18, (1963) [in Russian].
14. M. Talagrand, "Sharper bounds for Gaussian and empirical processes", Annals of Probability, 22(1), 28-76, (1994).
15. Aad W. van der Vaart and Jon A. Wellner, Weak Convergence and Empirical Processes, Springer, New York, 1996.
16. Frederick A. Valentine, Convex Sets, McGraw-Hill, San Francisco, 1964.
17. L. P. Vlasov, "Approximative Properties of Sets in Normed Linear Spaces," Russian Mathematical Surveys, 28(6), 1-66, (1973).