Abstract Machine learning has become a pivotal tool for many projects in computational
biology, bioinformatics, and health informatics. Nevertheless, beginners and biomedical …

The fields of medicine science and health informatics have made great progress recently
and have led to in-depth analytics that is demanded by generation, collection and …

Machine Learning (ML) techniques are pervasive tools in various emerging commercial
applications, but have to be accommodated by powerful computer systems to process very …

Machine Learning (ML) tasks are becoming pervasive in a broad range of applications, and
in a broad range of systems (from embedded systems to data centers). As computer …

Data clustering is one of the most studied data mining tasks. It aims, through various
methods, to discover previously unknown groups within the data sets. In the past years …

A growing number of commercial and enterprise systems increasingly rely on compute-
intensive Machine Learning (ML) algorithms. While the demand for these compute-intensive …

In this study, an Internet of Things (IoT)-based analysis system is proposed, which can be
used to design a consumer electronic device. This IoT-based analysis system will alert the …

In recent years the computing landscape has seen an increasing shift towards specialized
accelerators. Field programmable gate arrays (FPGAs) are particularly promising for the …

The DNA microarrays are used to monitor the expression levels of significant genes. Most of
the microarray data are assumed to be high dimensional, redundant, and noisy. This paper …

The growing scale and complexity of Machine Learning (ML) algorithms has resulted in
prevalent use of distributed general-purpose systems. In a rather disjoint effort, the …