This paper addresses the question of producing modular sequential imperative code from synchronous data-flow networks. Precisely, given a system with several input and output flow...
We present a fully connectionist system for the learning of first-order logic programs and the generation of corresponding models: Given a program and a set of training examples,...
As distributed computing systems grow in size, complexity and variety of application, the problem of protecting sensitive data from unauthorized disclosure and tampering becomes i...
Estimation of static and dynamic energy of caches is critical for high-performance low-power designs. Commercial CAD tools performing energy estimation statically are not aware of...
Shrikanth Ganapathy, Ramon Canal, Antonio Gonz&aac...
We propose a Gaussian process (GP) framework for robust inference in which a GP prior on the mixing weights of a two-component noise model augments the standard process over laten...