Bidimensionality theory was introduced by Demaine et al. [JACM 2005 ] as a framework to obtain algorithmic results for hard problems on minor closed graph classes. The theory has ...
Clustering constitutes an ubiquitous problem when dealing with huge data sets for data compression, visualization, or preprocessing. Prototype-based neural methods such as neural g...
Alexander Hasenfuss, Barbara Hammer, Fabrice Rossi
Abstract— Our main goal in this paper is to set the foundations of a general continuous-domain framework for designing steerable, reversible signal transformations (a.k.a. frames...
Model-based clustering of motion trajectories can be posed as the problem of learning an underlying mixture density function whose components correspond to motion classes with dif...
In this paper, we compare the architectural perspectives of the Wave Field Synthesis (WFS) 3D-audio algorithm mapped on three different platforms: a General Purpose Processor (GP...