We develop a framework for the image segmentation problem based on a new graph-theoretic formulation of clustering. The approach is motivated by the analogies between the intuitiv...
As a general framework to determine a collision-free feedback motion strategies, the Random Neighborhood Graph (RNG) approach [19] defines a global navigation function over an ap...
A general framework is proposed for gradient boosting in supervised learning problems where the loss function is defined using a kernel over the output space. It extends boosting ...
A semi-visual framework for the speci cation of syntax and semantics of imperative programming languages, called Montages, was proposed in an earlier work by the authors. The prima...
Matthias Anlauff, Philipp W. Kutter, Alfonso Piera...
This work presents a new perspective on characterizing the similarity between elements of a database or, more generally, nodes of a weighted, undirected, graph. It is based on a M...