An Outer-approximation Guided Optimization Approach for Constrained Neural Network Inverse Problems

24 Feb 2020 Myun-Seok Cheon

This paper discusses an outer-approximation guided optimization method for constrained neural network inverse problems with rectified linear units. The constrained neural network inverse problems refer to an optimization problem to find the best set of input values of a given trained neural network in order to produce a predefined desired output in presence of constraints on input values... (read more)

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