Clustering is inherently a difficult task and is made even more difficult when the selection of relevant features is also an issue. In this paper, we propose an approach for simult...
The construction of good, finite-length, LDPC codes is currently an attractive research area. Reducing attention to the Binary Erasure Channel (BEC), this problem translates into t...
Dejan Vukobratovic, Aleksandar Djurendic, Vojin Se...
Background: The Ensembl web site has provided access to genomic information for almost 10 years. During this time the amount of data available through Ensembl has grown dramatical...
Anne Parker, Eugene Bragin, Simon Brent, Bethan Pr...
Ensemble learning algorithms such as boosting can achieve better performance by averaging over the predictions of some base hypotheses. Nevertheless, most existing algorithms are ...
Clustering Stability methods are a family of widely used model selection techniques applied in data clustering. Their unifying theme is that an appropriate model should result in ...