Clustering, in data mining, is useful to discover distribution patterns in the underlying data. Clustering algorithms usually employ a distance metric based (e.g., euclidean) simi...
A novel method and a framework called Memory-Based Forecasting are proposed to forecast complex and timevarying natural patterns with the goal of supporting experts' decision...
Tensor-based morphometry (TBM) is an analysis technique where anatomical information is characterized by means of the spatial transformations between a customized template and obse...
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...
We consider data dissemination in a peer-to-peer network, where each user wishes to obtain some subset of the available information objects. In most of the modern algorithms for su...