Compressive sensing (CS) exploits the sparsity present in many common signals to reduce the number of measurements needed for digital acquisition. With this reduction would come, ...
Mark A. Davenport, Jason N. Laska, John R. Treichl...
Ubiquitous Knowledge Discovery is a new research area at the intersection of machine learning and data mining with mobile and distributed systems. In this paper the main character...
We are developing a set of ontologies that deal with vector-borne diseases and the arthropod vectors that transmit them. For practical reasons (application priorities), we initiat...
To understand the functional connectivity of neural networks, it is important to develop simple and incisive descriptors of multineuronal firing patterns. Analysis at the pairwise...
Triangle counting is an important problem in graph mining. Two frequently used metrics in complex network analysis which require the count of triangles are the clustering coefficie...