In this paper, we propose a new Distributed Cooperation and Diversity Combining framework. Our focus is heterogeneous networks with devices equipped with two types of radio frequen...
Ensembles of learning machines have been formally and empirically shown to outperform (generalise better than) single predictors in many cases. Evidence suggests that ensembles ge...
The execution performance of an information gathering plan can suffer significantly due to remote I/O latencies. A streaming dataflow model of execution addresses the problem to s...
Probabilistic branching node inference is an important step for analyzing branching patterns involved in many anatomic structures. We propose combining machine learning techniques...
Haibin Ling, Michael Barnathan, Vasileios Megalooi...
Biological systems consist of many components and interactions between them. In Systems Biology the principal problem is modeling complex biological systems and reconstructing inte...
Marenglen Biba, Stefano Ferilli, Nicola Di Mauro, ...