General dissimilarity-based learning approaches have been proposed for dissimilarity data sets [11, 10]. They arise in problems in which direct comparisons of objects are made, e....
Recent work has shown that one can learn the structure of Gaussian Graphical Models by imposing an L1 penalty on the precision matrix, and then using efficient convex optimization...
Recognizing useful modular robot configurations composed of hundreds of modules is a significant challenge. Matching a new modular robot configuration to a library of known configu...
Michael Park, Sachin Chitta, Alex Teichman, Mark Y...
In this paper we deal with making drawings of clustered hierarchical graphs nicer. Given a planar graph G = (V, E) with an assignment of the vertices to horizontal layers, a plane ...
Abstract. The study of (minimally) rigid graphs is motivated by numerous applications, mostly in robotics and bioinformatics. A major open problem concerns the number of embeddings...
Ioannis Z. Emiris, Elias P. Tsigaridas, Antonios V...