Function Learning from Interpolation

Combinatorics Probability and Computing

Volumn 9, Issue 3, 2000, Pages 213-225

  Anthony, Martin ^a   Bartlett, Peter L ^b  

^a LONDON SCHOOL OF ECONOMICS   (United Kingdom)

^b AUSTRALIAN NATIONAL UNIVERSITY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 0034414856     PISSN: 09635483     EISSN: None     Source Type: Journal    
DOI: 10.1017/S0963548300004247     Document Type: Article

References (14)

1. Alon, N., Ben-David, S., Cesa-Bianchi, N. and Haussler, D. (1997) Scale-sensitive dimensions, uniform convergence, and learnability. J. Assoc. Comput. Mach. 44 615-631.
2. Anthony, M. and Biggs, N. (1992) Computational Learning Theory: An Introduction, Cambridge University Press.
3. Bartlett, P. L., Long, P. M. and Williamson, R. C. (1994) Fat-shattering and the learnability of real-valued functions. In Proc. Seventh Annual ACM Conference on Computational Learning Theory, ACM Press, New York.
4. Ben-David, S., Cesa-Bianchi, N., Haussler, D. and Long, P. (1995) Characterizations of learnability for classes of {0,...,n}-valued functions. J. Comput. System Sci. 50 74-86. (An earlier version appeared in Proc. Fifth Annual ACM Workshop on Computational Learning Theory, ACM Press, New York.)
5. Ben-David, S., Cesa-Bianchi, N., Haussler, D. and Long, P. (1995) Characterizations of learnability for classes of {0,...,n}-valued functions. J. Comput. System Sci. 50 74-86. (An earlier version appeared in Proc. Fifth Annual ACM Workshop on Computational Learning Theory, ACM Press, New York.)
6. Blumer, A., Ehrenfeucht, A., Haussler, D. and Warmuth, M. K. (1989) Learnability and the Vapnik-Chervonenkis dimension. J. Assoc. Comput. Mach. 36 929-965.
7. Dudley, R. M., Giné, E. and Zinn, J. (1991) Uniform and universal Glivenko-Cantelli classes. J. Theoret. Probab. 4 485-510.
8. Ehrenfeucht, A., Haussler, D., Kearns, M. and Valiant, L. (1989) A general lower bound on the number of examples needed for learning. Inform. Comput. 82 247-261.
9. Haussler, D. (1992) Decision theoretic generalizations of the PAC model for neural net and other learning applications. Inform. Comput. 100 78-150.
10. Kearns, M. J. and Schapire, R. E. (1994) Efficient distribution-free learning of probabilistic concepts. J. Comput. System Sci. 48 464-497.
11. Kolmogorov, A. N. and Tihomirov, V. M. (1961) ∈-entropy and ∈-capacity of sets in functional spaces. AMS Translations Ser. 2 17 277-364.
12. Natarajan, B. K. (1993) Occam's razor for functions. In Proc. Sixth Annual Workshop on Computational Learning Theory, ACM Press, New York, pp. 370-376.
13. Pollard, D. (1984) Convergence of Stochastic Processes, Springer.
14. Vapnik, V. N. and Chervonenkis, A. Ya. (1971) On the uniform convergence of relative frequencies of events to their probabilities. Theory of Probability and its Applications 16 264-280.