Analytic Network Learning

20 Nov 2018Kar-Ann Toh

Based on the property that solving the system of linear matrix equations via the column space and the row space projections boils down to an approximation in the least squares error sense, a formulation for learning the weight matrices of the multilayer network can be derived. By exploiting into the vast number of feasible solutions of these interdependent weight matrices, the learning can be performed analytically layer by layer without needing of gradient computation after an initialization... (read more)

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