On the Conditions for the Existence of Perfect Learning and Power Law Behaviour in Learning from Stochastic Examples by Ising Perceptrons
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In a previous work, we studied learning from stochastic examples by perceptrons with Ising weights in the framework of statistical mechanics. Employing the one-step replica symmetry breaking ansatz, types of behaviour of learning curves were classified according to a certain local property of the rules by which examples were drawn. Further, the conditions for the existence of the perfect learning, together with other behaviour of the learning curves, were given. In this paper, we give a detailed derivation of these results and a further argument regarding perfect learning. We also present the results of extensive numerical calculations.
- 社団法人日本物理学会の論文
- 2002-08-15
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