Like in many other research areas, deep learning (DL) is increasingly adopted in music
recommendation systems (MRS). Deep neural networks are used in this domain particularly …

We provide a survey of the field of Music Information Retrieval (MIR), in particular paying
attention to latest developments, such as semantic auto-tagging and user-centric retrieval …

Customer churn prediction is very important for e-commerce enterprises to formulate
effective customer retention measures and implement successful marketing strategies …

The task of estimating the fundamental frequency of a monophonic sound recording, also
known as pitch tracking, is fundamental to audio processing with multiple applications in …

Abstract k-nearest neighbors (k-NN) is a well-known classification algorithm that is widely
used in different domains. Despite its simplicity, effectiveness and robustness, k-NN is …

Music genre recognition based on visual representation has been successfully explored
over the last years. Classifiers trained with textural descriptors (eg, Local Binary Patterns …

Recent advances in artificial intelligence demand an automated framework for the
development of versatile brain–computer interface (BCI) systems. In this article, we …

Background: Analysis and classification of extensive medical data (eg
electroencephalography (EEG) signals) is a significant challenge to develop effective brain …

In machine learning (ML), ensemble methods-such as bagging, boosting, and stacking-are
widely-established approaches that regularly achieve top-notch predictive performance …

An adversary is an agent designed to make a classification system perform in some
particular way, eg, increase the probability of a false negative. Recent work builds …