We consider the computational problem of finding nearest neighbors in general metric spaces. Of particular interest are spaces that may not be conveniently embedded or approximate...
Iterative shrinkage of sparse and redundant representations are at the heart of many state of the art denoising and deconvolution algorithms. They assume the signal is well approx...
We present an evolving neural network model in which synapses appear and disappear stochastically according to bio-inspired probabilities. These are in general nonlinear functions ...
In this paper we introduce an adaptive technique for compressing small quantities of text which are organized as a rooted directed graph. We impose a constraint on the technique s...
Medial surfaces are popular representations of 3D objects in vision, graphics and geometric modeling. They capture relevant symmetries and part hierarchies and also allow for deta...