Bayesian Networks are today used in various fields and domains due to their inherent ability to deal with uncertainty. Learning Bayesian Networks, however is an NP-Hard task [7]....
This paper addresses distributed task allocation in complex scenarios modeled using the distributed constraint optimization problem (DCOP) formalism. We propose and evaluate a nov...
Paulo Roberto Ferreira Jr., Felipe S. Boffo, Ana L...
In this paper we present a design space exploration flow to achieve energy efficiency for streaming applications on MPSoCs while meeting the specified throughput constraints. The ...
Concept drifting is an important and challenging research issue in the field of machine learning. This paper mainly addresses the issue of semantic concept drifting in time series...
Many Web applications are based on dynamic interactions between Web components exchanging flows of information. Such a situation arises for instance in mashup systems or when moni...