On the Mappings of Optimization Problems to Neural Networks

In the past, neural networks have often performed poorly on optimization problems, often because the mappings are deficient (see [11, 1] for example). This work is motivated by the need to study better the mappings of optimization problems to neural networks, and builds on some early work in this area [17]. Its technical roots are in the topic of approximation-preserving reductions in computational complexity theory.