M. Golea and M. Marchand. Average case analysis of the clipped Hebb rule for nonoverlapping Perceptron networks. In Proceedings of the Sixth Annual Workshop on Computational Learning Theory (COLT-93), pages 151--157, 1993. Home/Search Document Details and Download
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Characterizing Rational versus Exponential Learning Curves - Schuurmans (1995) (2 citations) (Correct)
....domain distribution P is known a priori. Given these stronger assumptions, many researchers have shown that both rational and exponential learning curves are possible. For example, exponential convergence has been demonstrated in many distribution specific analyses of particular concept spaces [GM93, BL91, PS90, SSSD90, SST91], and rational convergence has been demonstrated for other spaces [OH91] 5 This paper shows how, in a general way, this dichotomy can still be revealed under much weaker assumptions. We also draw a clean boundary between these two modes of convergence in terms of a simple structural property of ....
M. Golea and M. Marchand. Average case analysis of the clipped Hebb rule for nonoverlapping Perceptron networks. In Proceedings of the Sixth Annual Workshop on Computational Learning Theory (COLT-93), pages 151--157, 1993.
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