We developed a system that extracts and visualizes the network structures from relational data on spreadsheets. Visualization through network diagrams obtained from relational data...
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...
Abstract. The problem of clustering data can be formulated as a graph partitioning problem. In this setting, spectral methods for obtaining optimal solutions have received a lot of...
Marcus Weber, Wasinee Rungsarityotin, Alexander Sc...
A k-set structure over data streams is a bounded-space data structure that supports stream insertion and deletion operations and returns the set of (item, frequency) pairs in the s...
We introduce a robust and efficient framework called CLUMP (CLustering Using Multiple Prototypes) for unsupervised discovery of structure in data. CLUMP relies on finding multip...