We exhibit an explicitly computable ‘pseudorandom’ generator stretching l bits into m(l) = lΩ(log l) bits that look random to constant-depth circuits of size m(l) with log m...
We describe a new approach for understanding the difficulty of designing efficient learning algorithms. We prove that the existence of an efficient learning algorithm for a circui...
higher levels of abstraction, due to the still increasing design complexities that can be expected in the near future. Behavioral synthesis can play a key role in this prospect, as...
We present an accurate and efficient method for extraction of parasitic capacitances in submicron integrated circuits. The method uses a 3-D finite element model in which the cond...
Abstract. Over the last decade, first-order constraints have been efficiently used in the artificial intelligence world to model many kinds of complex problems such as: scheduling,...