Patient similarity networks (PSNs), where patients are represented as nodes and their
similarities as weighted edges, are being increasingly used in clinical research. These …

Our research work describes a team of human Digital Twins (DTs), each tracking fitness-
related measurements describing an athlete's behavior in consecutive days (eg food …

Recently, a great deal of research work has been devoted to the development of algorithms
to estimate the intrinsic dimensionality (id) of a given dataset, that is the minimum number of …

In order to realize the automatic epileptic seizure detection, feature extraction and
classification of electroencephalogram (EEG) signals are performed on the interictal, the pre …

Multilinear/tensor extensions of manifold learning based algorithms have been widely used
in computer vision and pattern recognition. This paper first provides a systematic analysis of …

Twitter is one of the most popular micro-blogging services in the world, often studied in the
context of political opinion mining for its peculiar nature of online public discussion platform …

Existing learning models for classification of imbalanced data sets can be grouped as either
boundary-based or nonboundary-based depending on whether a decision hyperplane is …

The two-dimensional linear discriminant analysis (2D-LDA) algorithm was originally
proposed in the context of face image processing for the extraction of features with maximal …

Near infrared spectra of apples contain the most useful information of the soluble solids
content and firmness of apples. A new feature extraction method, called sorting discriminant …

The success of many machine learning (ML) methods depends crucially on having large
amounts of labeled data. However, obtaining enough labeled data can be expensive, time …