We study a sparse coding learning algorithm that allows for a simultaneous learning of the data sparseness and the basis functions. The algorithm is derived based on a generative m...
In this work an improvement of an initial approach to design Artificial Neural Networks to forecast Time Series is tackled, and the automatic process to design Artificial Neural N...
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...
Rising energy costs in large data centers are driving an agenda for energy-efficient computing. In this paper, we focus on the role of database software in affecting, and, ultimat...
Background: High-throughput methods for detecting protein-protein interactions enable us to obtain large interaction networks, and also allow us to computationally identify the as...