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NIPS
2004
15 years 7 months ago
Proximity Graphs for Clustering and Manifold Learning
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...
Miguel Á. Carreira-Perpiñán, ...
CORR
2010
Springer
143views Education» more  CORR 2010»
15 years 6 months ago
Quasi-randomness of graph balanced cut properties
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...
Hao Huang, Choongbum Lee
DCG
2002
66views more  DCG 2002»
15 years 6 months ago
Generation of Oriented Matroids - A Graph Theoretical Approach
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...
Lukas Finschi, Komei Fukuda
DAM
2008
90views more  DAM 2008»
15 years 6 months ago
Polarity of chordal graphs
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...
ICML
2005
IEEE
16 years 7 months ago
Error bounds for correlation clustering
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...
Thorsten Joachims, John E. Hopcroft