We consider the topographic clustering task and focus on the problem of its evaluation, which enables to perform model selection: topographic clustering algorithms, from the origin...
Non-parametric data representation can be done by means of a potential function. This paper introduces a methodology for finding modes of the potential function. Two different me...
Navigation in and access to the contents of digital audio archives have become increasingly important topics in Information Retrieval. Both private and commercial music collection...
We present a theoretical study on the discriminative clustering framework, recently proposed for simultaneous subspace selection via linear discriminant analysis (LDA) and cluster...
Identifying the appropriate kernel function/matrix for a given dataset is essential to all kernel-based learning techniques. A variety of kernel learning algorithms have been prop...