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
Wireless sensor networks generate a vast amount of data. This data, however, must be sparingly extracted to conserve energy, usually the most precious resource in battery-powered ...
Adam Silberstein, Carla Schlatter Ellis, Jun Yang ...
The deconvolution of blurred and noisy satellite images is an ill-posed inverse problem, which can be regularized within a Bayesian context by using an a priori model of the recon...
Subspace segmentation is the task of segmenting data
lying on multiple linear subspaces. Its applications in
computer vision include motion segmentation in video,
structure-from...
The core vector machine (CVM) is a recent approach for scaling up kernel methods based on the notion of minimum enclosing ball (MEB). Though conceptually simple, an efficient impl...