Clustering methods can be either data-driven or need-driven. Data-driven methods intend to discover the true structure of the underlying data while need-driven methods aims at org...
The increasing use of computers for saving valuable data imposes stringent reliability constraints on storage systems. Reliability improvement via use of redundancy is a common pr...
In the discrete filtering problem, a data sequence over a finite alphabet is assumed to be corrupted by a discrete memoryless channel. The goal is to reconstruct the clean sequenc...
Erik Ordentlich, Tsachy Weissman, Marcelo J. Weinb...
Approximate Nearest Neighbor (ANN) methods such as Locality Sensitive Hashing, Semantic Hashing, and Spectral Hashing, provide computationally ecient procedures for nding objects...
Background: Web Services and Workflow Management Systems can support creation and deployment of network systems, able to automate data analysis and retrieval processes in biomedic...