Many machine learning algorithms for clustering or dimensionality reduction take as input a cloud of points in Euclidean space, and construct a graph with the input data points as...
Quasi-random graphs can be informally described as graphs whose edge distribution closely resembles that of a truly random graph of the same edge density. Recently, Shapira and Yu...
We discuss methods for the generation of oriented matroids and of isomorphism classes of oriented matroids. Our methods are based on single element extensions and graph theoretica...
Polar graphs are a common generalization of bipartite, cobipartite, and split graphs. They are defined by the existence of a certain partition of vertices, which is NPcomplete to ...
Tinaz Ekim, Pavol Hell, Juraj Stacho, Dominique de...
This paper presents a learning theoretical analysis of correlation clustering (Bansal et al., 2002). In particular, we give bounds on the error with which correlation clustering r...