Exploiting Layerwise Convexity of Rectifier Networks with Sign Constrained Weights

14 Nov 2017Senjian AnFarid BoussaidMohammed BennamounFerdous Sohel

By introducing sign constraints on the weights, this paper proposes sign constrained rectifier networks (SCRNs), whose training can be solved efficiently by the well known majorization-minimization (MM) algorithms. We prove that the proposed two-hidden-layer SCRNs, which exhibit negative weights in the second hidden layer and negative weights in the output layer, are capable of separating any two (or more) disjoint pattern sets... (read more)

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