Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-...
Christopher Leckie, James C. Bezdek, Kotagiri Rama...
In this paper, we investigate to which extent the "raw" mapping of Taylor series coefficients into jet-space can be used as a "language" for describing local i...
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...
It is well known that local patterns are at the core of a lot of knowledge which may be discovered from data. Nevertheless, use of local patterns is limited by their huge number an...
Volunteer Computing is becoming a new paradigm not only for the Computational Grid, but also for institutions using production-level Data Grids because of the enormous storage pot...
Jesus Luna, Michail Flouris, Manolis Marazakis, An...