Several real-world applications need to effectively manage and reason about large amounts of data that are inherently uncertain. For instance, pervasive computing applications mus...
Daisy Zhe Wang, Eirinaios Michelakis, Minos N. Gar...
We address possible limitations of publicly available data sets of yeast gene expression. We study the predictability of known regulators via time-series analysis, and show that l...
Abstract— We propose the Multi-resolution Correlation Cluster detection (MrCC), a novel, scalable method to detect correlation clusters able to analyze dimensional data in the ra...
Robson Leonardo Ferreira Cordeiro, Agma J. M. Trai...
Sampling is a widely used technique to increase efficiency in database and data mining applications operating on large dataset. In this paper we present a scalable sampling imple...
We describe a higher-orderspectralanalysis-basedapproach for detecting people by recognizing human motion such as walking or running. The periodic attribute of human motion lends ...