We directly lower bound the information capacity for channels with i.i.d. deletions and duplications. Our approach differs from previous work in that we focus on the information ca...
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
Background: Ab initio protein structure prediction methods generate numerous structural candidates, which are referred to as decoys. The decoy with the most number of neighbors of...
Bayesian network classifiers have been widely used for classification problems. Given a fixed Bayesian network structure, parameters learning can take two different approaches: ge...
Jiang Su, Harry Zhang, Charles X. Ling, Stan Matwi...
The development of application specific instruction set processors comprises several design phases: architecture exploration, software tools design, system verification and design...
Oliver Schliebusch, Andreas Hoffmann, Achim Nohl, ...