Abstract. In this paper we present a coarse-grained parallel algorithm, CONQUEST, for constructing boundederror summaries of high-dimensional binary attributed data in a distribute...
Existing density-based data stream clustering algorithms use a two-phase scheme approach consisting of an online phase, in which raw data is processed to gather summary statistics...
Agostino Forestiero, Clara Pizzuti, Giandomenico S...
This paper describes the design and implementation on MIMD parallel machines of P-AutoClass, a parallel version of the AutoClass system based upon the Bayesian method for determini...
We describe a framework for automatically selecting a summary set of photos from a large collection of geo-referenced photographs. Such large collections are inherently difficult ...
Alexander Jaffe, Mor Naaman, Tamir Tassa, Marc Dav...
Support vector machines (SVMs) have been promising methods for classification and regression analysis because of their solid mathematical foundations which convey several salient ...