Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

	1	Noga Alon, Shai Ben-David, Nicol6 Cesa-Bianchi, and David Haussler. Scale-sensitive dimensions, uniform convergence, and learnability. In Proceedings of the 3~th Symposium on Foundations of Computer Science, pages 292-302. IEEE Computer Society Press, 1993.
	2	Peter L. Bartlett , Philip M. Long , Robert C. Williamson, Fat-shattering and the learnability of real-valued functions, Proceedings of the seventh annual conference on Computational learning theory, p.299-310, July 12-15, 1994, New Brunswick, New Jersey, United States  [doi>10.1145/180139.181158]
	3	Ethan J. Bernstein, Absolute error bounds for learning linear functions online, Proceedings of the fifth annual workshop on Computational learning theory, p.160-163, July 27-29, 1992, Pittsburgh, Pennsylvania, United States  [doi>10.1145/130385.130403]
	4	Anselm Blumer , A. Ehrenfeucht , David Haussler , Manfred K. Warmuth, Learnability and the Vapnik-Chervonenkis dimension, Journal of the ACM (JACM), v.36 n.4, p.929-965, Oct. 1989  [doi>10.1145/76359.76371]
	5	Nicolo Cesa-Bianchi , Philip M. Long , Manfred K. Warmuth, WORST-CASE QUADRATIC LOSS BOUNDS FOR ON-LINE PREDICTION OF LINEAR FUNCTIONS BY GRADIENT DESCENT, University of California at Santa Cruz, Santa Cruz, CA, 1993
	6	Andrzej Ehrenfeucht , David Haussler, A general lower bound on the number of examples needed for learning, Information and Computation, v.82 n.3, p.247-261, Sep. 1989  [doi>10.1016/0890-5401(89)90002-3]
	7	David Haussler, Decision theoretic generalizations of the PAC model for neural net and other learning applications, Information and Computation, v.100 n.1, p.78-150, Sept. 1992  [doi>10.1016/0890-5401(92)90010-D]
	8	Michael J. Kearns , Robert E. Schapire, Efficient distribution-free learning of probabilistic concepts, Journal of Computer and System Sciences, v.48 n.3, p.464-497, June 1994  [doi>10.1016/S0022-0000(05)80062-5]
	9	Nick Littlestone, From on-line to batch learning, Proceedings of the second annual workshop on Computational learning theory, p.269-284, December 1989, Santa Cruz, California, United States
	10	J. Mycielski. A learning algorithm for linear operators. Proceedings of the American Mathematical Society, 103(2):547-550, 1988.
	11	Hans Ulrich Simon, Bounds on the number of examples needed for learning functions, Proceedings of the first European conference on Computational learning theory, p.83-94, October 1994, Royal Holloway, Univ. of London, United Kingdom

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