There is growing interest in applying Bayesian techniques to NLP problems. There are a number of different estimators for Bayesian models, and it is useful to know what kinds of t...
—This paper addresses, from a probabilistic point of view, the issue of switching activity estimation in combinational circuits under the zero-delay model. As the main theoretica...
Temporal difference (TD) algorithms are attractive for reinforcement learning due to their ease-of-implementation and use of "bootstrapped" return estimates to make effi...
As research begins to explore potential nanotechnologies for future post-CMOS integrated systems, modeling and simulation environments must be developed that can accommodate the c...
In this paper we present a simple yet accurate model to forecast electricity load with Artificial Neural Networks (ANNs). We analyze the problem domain and choose the most adequat...