Practical data mining rarely falls exactly into the supervised learning scenario. Rather, the growing amount of unlabeled data poses a big challenge to large-scale semi-supervised...
Many techniques in the social sciences and graph theory deal with the problem of examining and analyzing patterns found in the underlying structure and associations of a group of ...
Jeremy Kubica, Andrew W. Moore, David Cohn, Jeff G...
Most real-world data is stored in relational form. In contrast, most statistical learning methods work with "flat" data representations, forcing us to convert our data i...
Lise Getoor, Nir Friedman, Daphne Koller, Benjamin...
Abstract. Diagnostic and classification algorithms play an important role in data analysis, with applications in areas such as health care, fault diagnostics, or benchmarking. Bran...
Mauro Barni, Pierluigi Failla, Vladimir Kolesnikov...
The advent of new parallel architectures has increased the need for parallel optimizing compilers to assist developers in creating efficient code. OpenUH is a state-of-the-art opt...
Lei Huang, Deepak Eachempati, Marcus W. Hervey, Ba...