We describe an algorithm for converting linear support vector machines and any other arbitrary hyperplane-based linear classifiers into a set of non-overlapping rules that, unlike...
The reinforcement learning problem can be decomposed into two parallel types of inference: (i) estimating the parameters of a model for the underlying process; (ii) determining be...
— Timed Continuous Petri Net (TCPN) systems are piecewise linear models with input constraints that can approximate the dynamical behavior of a class of timed discrete event syst...
This paper proposes a framework for modeling and controlling systems described by interdependent physical laws, logic rules, and operating constraints, denoted as mixed logical dy...
We describe an optimize-and-dispatch approach for delivering pay-per-impression advertisements in online advertising. The platform provider for an advertising network commits to s...