Classical statistical learning theory studies the generalisation performance of machine learning algorithms rather indirectly. One of the main detours is that algorithms are studi...
In this paper, we concentrate on the expressive power of hierarchical structures in neural networks. Recently, the so-called SplitNet model was introduced. It develops a dynamic n...
Our research is motivated by the scaleability, availability, and extensibility challenges in deploying open systems based, enterprise operational applications. We present Delta...
Van Oleson, Karsten Schwan, Greg Eisenhauer, Beth ...
Visualizing large-scale online social network is a challenging yet essential task. This paper presents HiMap, a system that visualizes it by clustered graph via hierarchical group...
Lei Shi, Nan Cao, Shixia Liu, Weihong Qian, Li Tan...
Map-reduce framework has received a significant attention and is being used for programming both large-scale clusters and multi-core systems. While the high productivity aspect of ...