Failures of any type are common in current datacenters, partly due to the higher scales of the data stored. As data scales up, its availability becomes more complex, while differe...
Nicolas Bonvin, Thanasis G. Papaioannou, Karl Aber...
This work studies the impact of using dynamic information as features in a machine learning algorithm for the prediction task of classifying critically ill patients in two classes ...
Hybrid architectures, which are composed of a conventional processor closely coupled with reconfigurable logic, seem to combine the advantages of both types of hardware. They pres...
Background: There is a vast need to find clinically applicable protein biomarkers as support in cancer diagnosis and tumour classification. In proteomics research, a number of met...
Abstract--Until quite recently, extending Phrase-based Statistical Machine Translation (PBSMT) with syntactic knowledge caused system performance to deteriorate. The most recent su...