In this survey we discuss the task of hierarchical classification. The literature about this field
is scattered across very different application domains and for that reason research in one …

One crucial test for any quantitative model of the brain is to show that the model can be used
to accurately decode information from evoked brain activity. Several recent neuroimaging …

The two key challenges in hierarchical classification are to leverage the hierarchical
dependencies between the class-labels for improving performance, and, at the same time …

We argue that an evaluation of system behavior at the level of the music is required to
usefully address the fundamental problems of music genre recognition (MGR), and indeed …

Much work is focused upon music genre recognition (MGR) from audio recordings, symbolic
data, and other modalities. While reviews have been written of some of this work before, no …

Protein function prediction is a complex multiclass multilabel classification problem,
characterized by multiple issues such as the incompleteness of the available annotations …

Music is present in everyday life and used for a wide range of objectives. Musical databases
have considerably increased in number and size over the past years, therefore, the …

During the last 10 years there has been a dramatic shift in how music is produced,
distributed, and consumed. A combination of advances in digital storage, audio …

La classification automatique de la musique est un vaste domaine de recherche,
multidisciplinaire par nature, et qui donne lieu à des avancées significatives tant du point de …

This paper presents two novel hierarchical classification methods which are extensions of a
previously proposed selective classifier top-down approach, which consists of selecting …