Recently, the Sparse Matrix Transform (SMT) has been proposed as a tool for estimating the eigen-decomposition of high dimensional data vectors [1]. The SMT approach has two major...
Leonardo R. Bachega, Guangzhi Cao, Charles A. Boum...
Learning Bayesian network structure from large-scale data sets, without any expertspecified ordering of variables, remains a difficult problem. We propose systematic improvements ...
Data flow models are used for specifying and analysing signal processing and streaming applications. However, traditional data flow models are either not capable of expressing t...
Bart D. Theelen, Marc Geilen, Twan Basten, Jeroen ...
This paper describes a powerful method for dead code analysis and elimination in the presence of recursive data constructions. We describe partially dead recursive data using live...
Background: Identifying candidate genes in genetic networks is important for understanding regulation and biological function. Large gene expression datasets contain relevant info...
Anup Parikh, Eryong Huang, Christopher Dinh, Blaz ...