Most datasets in real applications come in from multiple sources. As a result, we often have attributes information about data objects and various pairwise relations (similarity) ...
We consider the task of performing anomaly detection in highly noisy multivariate data. In many applications involving real-valued time-series data, such as physical sensor data a...
Supervised learning deals with the inference of a distribution over an output or label space $\CY$ conditioned on points in an observation space $\CX$, given a training dataset $D$...
Abstract. We present the first (to our knowledge) approximation algorithm for tensor clustering—a powerful generalization to basic 1D clustering. Tensors are increasingly common...
Abstract—Because of the today’s market demand for highperformance, high-density portable hand-held applications, electronic system design technology has shifted the focus from ...