Dynamics of learning with restricted training sets

Coolen, Anthony C.C. and Saad, David (2000). Dynamics of learning with restricted training sets. Physical Review E, 62 (4), pp. 5444-5487.

Abstract

The dynamics of supervised learning in layered neural networks were studied in the regime where the size of the training set is proportional to the number of inputs. The evolution of macroscopic observables, including the two relevant performance measures can be predicted by using the dynamical replica theory. Three approximation schemes aimed at eliminating the need to solve a functional saddle-point equation at each time step have been derived.

Publication DOI: https://doi.org/10.1103/PhysRevE.62.5444
Divisions: Engineering & Applied Sciences > Mathematics
Additional Information: Copyright of American Physical Society
Uncontrolled Keywords: layered neural networks,learning dynamics,dynamically replica theory,Mathematical Physics,Physics and Astronomy(all),Condensed Matter Physics,Statistical and Nonlinear Physics
Published Date: 2000-10

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