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...
Learning software is not designed for data analysis and mining. Because usage data is not stored in a systematic way, its thorough analysis requires long and tedious preprocessing....
This paper presents a method for tight prediction of worst-case performance of data caches in highperformance real-time systems. Our approach is to distinguish between data struct...