In distributed data mining models, adopting a flat node distribution model can affect scalability. To address the problem of modularity, flexibility and scalability, we propose...
In the last few years, we have been witnessing an evergrowing need for continuous observation and monitoring applications. This need is driven by recent technological advances that...
Themis Palpanas, Vana Kalogeraki, Dimitrios Gunopu...
TCP can perform poorly in multi-hop wireless networks due to problems that arise with contention and mobility. Endto-end protocols are at an inherent disadvantage in trying to sol...
Obtaining an accurate multiple alignment of protein sequences is a difficult computational problem for which many heuristic techniques sacrifice optimality to achieve reasonable r...
We present a novel framework for multi-label learning that explicitly addresses the challenge arising from the large number of classes and a small size of training data. The key a...