Recently, several manifold learning algorithms have been proposed, such as ISOMAP (Tenenbaum et al., 2000), Locally Linear Embedding (Roweis & Saul, 2000), Laplacian Eigenmap ...
Abstract. Kernel based methods (such as k-nearest neighbors classifiers) for AI tasks translate the classification problem into a proximity search problem, in a space that is usu...
—Privacy-Preserving Authentication (PPA) is crucial for Radio Frequency Identifcation (RFID)-enabled applications. Without appropriate formal privacy models, it is difficult for...
In this paper, we study the problem of how to generate synthetic graphs matching various properties of a real social network with two applications, privacy preserving social netwo...
The soundness of clustering in the analysis of gene expression profiles and gene function prediction is based on the hypothesis that genes with similar expression profiles may imp...