Online monitoring of data streams poses a challenge in many data-centric applications, such as telecommunications networks, traffic management, trend-related analysis, webclick st...
The discovery of biclusters, which denote groups of items that show coherent values across a subset of all the transactions in a data set, is an important type of analysis perform...
Gaurav Pandey, Gowtham Atluri, Michael Steinbach, ...
In this paper, we propose a novel method for fast nearest neighbors retrieval in non-Euclidean and non-metric spaces. We organize the data into a hierarchical fashion that preserv...
Abstract. This paper presents algorithms and data structures that exploit a compositional and hierarchical specification to enable more efficient symbolic modelchecking. We encod...
Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is perfor...
Gert R. G. Lanckriet, Nello Cristianini, Peter L. ...