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KDD
2006
ACM
164views Data Mining» more  KDD 2006»
16 years 7 months ago
Sampling from large graphs
Given a huge real graph, how can we derive a representative sample? There are many known algorithms to compute interesting measures (shortest paths, centrality, betweenness, etc.)...
Jure Leskovec, Christos Faloutsos
SIAMDM
2008
79views more  SIAMDM 2008»
15 years 6 months ago
Testing Triangle-Freeness in General Graphs
In this paper we consider the problem of testing whether a graph is triangle-free, and more generally, whether it is H-free, for a fixed subgraph H. The algorithm should accept gr...
Noga Alon, Tali Kaufman, Michael Krivelevich, Dana...
ICALP
2011
Springer
14 years 10 months ago
Vertex Cover in Graphs with Locally Few Colors
In [13], Erd˝os et al. defined the local chromatic number of a graph as the minimum number of colors that must appear within distance 1 of a vertex. For any ∆ ≥ 2, there are ...
Fabian Kuhn, Monaldo Mastrolilli
KDD
2012
ACM
196views Data Mining» more  KDD 2012»
13 years 9 months ago
Chromatic correlation clustering
We study a novel clustering problem in which the pairwise relations between objects are categorical. This problem can be viewed as clustering the vertices of a graph whose edges a...
Francesco Bonchi, Aristides Gionis, Francesco Gull...
ECCV
2006
Springer
16 years 8 months ago
Robust Multi-body Motion Tracking Using Commute Time Clustering
Abstract. The presence of noise renders the classical factorization method almost impractical for real-world multi-body motion tracking problems. The main problem stems from the ef...
Huaijun Qiu, Edwin R. Hancock