Efficient learning of a data analysis task strongly depends on the data representation. Most
methods rely on (symmetric) similarity or dissimilarity representations by means of metric …

Musical difficulty estimation is an essential part of musical learning. Without a precise
estimate, a music learner cannot choose a piece to play according to their current level. This …

Prototype-based methods often display very intuitive classification and learning rules.
However, popular prototype based classifiers such as learning vector quantization (LVQ) are …

Exemplar based techniques such as affinity propagation represent data in terms of typical
exemplars. This has two benefits:(i) the resulting models are directly interpretable by …

Parent–daughter ratio: The ratio of rubidium (Rb) to strontium (Sr). The ratio is commonly
expressed as 87Rb/86Sr, where the unstable Rb-87 isotope is referred to as the parent …

Since they represent a model in terms of few typical representatives, prototype based
learning such as learning vector quantization (LVQ) constitutes a directly interpretable …

Indefinite similarity measures can be frequently found in bio-informatics by means of
alignment scores, but are also common in other fields like shape measures in image …

For centuries, sheet music scores have been the traditional way to preserve and
disseminate Western music works. Nowadays, their content can be encoded in digital …

The generative topographic mapping (GTM) has been proposed as a statistical model to
represent high-dimensional data by a distribution induced by a sparse lattice of points in a …

We present a novel compression-based method for measuring similarity between
sequences of symbolic, polyphonic music. The method is based on mapping the values of …