The Cavity Method: Applications to Learning and Retrieval in Neural Networks
نویسنده
چکیده
Using the cavity method I derive the microscopic equations and their stability condition for learning in neural networks. Iterating the microscopic equations provides a general algorithm for network learning, supported by simulations in the maximally stable perceptron and the committee tree. Macroscopic results agree with the replica theory and the Almeida-Thouless stability condition. They are applied to derive the evolution equations of the overlap order parameter and the noise parameter in the retrieval dynamics of feedforward neural networks, results connrmed by simulations.
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تاریخ انتشار 1995