Abstract: Disclosed are systems, methods, and other implementations that include a machine-implemented artificial neural network including a plurality of nodes, with the nodes forming at plurality of layers including an input layer, at least one hidden layer, and an output layer, and a plurality of links, with each link coupling a corresponding source node and a receiving node. At least one link is configured to evaluate a piecewise linear function of a value provided by a first source node, from the plurality of nodes, to yield a value for a first receiving node coupled to the at least one link. Each node of a hidden layer is configured to aggregate values provided by links for which that node is the receiving node of the link, with the first receiving node providing non-linear output resulting, in part, from the at least one link configured to evaluate the piecewise linear function.

Abstract: Disclosed are systems, methods, and other implementations that include a machine-implemented artificial neural network including a plurality of nodes, with the nodes forming at plurality of layers including an input layer, at least one hidden layer, and an output layer, and a plurality of links, with each link coupling a corresponding source node and a receiving node. At least one link is configured to evaluate a piecewise linear function of a value provided by a first source node, from the plurality of nodes, to yield a value for a first receiving node coupled to the at least one link Each node of a hidden layer is configured to aggregate values provided by links for which that node is the receiving node of the link, with the first receiving node providing non-linear output resulting, in part, from the at least one link configured to evaluate the piecewise linear function.