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» Approximate Discovery of Random Graphs
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CVPR
2012
IEEE
11 years 10 months ago
Scalable k-NN graph construction for visual descriptors
The k-NN graph has played a central role in increasingly popular data-driven techniques for various learning and vision tasks; yet, finding an efficient and effective way to con...
Jing Wang, Jingdong Wang, Gang Zeng, Zhuowen Tu, R...
MST
2010
187views more  MST 2010»
13 years 2 months ago
Distributed Approximation of Capacitated Dominating Sets
We study local, distributed algorithms for the capacitated minimum dominating set (CapMDS) problem, which arises in various distributed network applications. Given a network graph...
Fabian Kuhn, Thomas Moscibroda
CORR
2010
Springer
107views Education» more  CORR 2010»
13 years 6 months ago
Maximum Betweenness Centrality: Approximability and Tractable Cases
The Maximum Betweenness Centrality problem (MBC) can be defined as follows. Given a graph find a k-element node set C that maximizes the probability of detecting communication be...
Martin Fink, Joachim Spoerhase
KDD
2007
ACM
244views Data Mining» more  KDD 2007»
14 years 8 months ago
A Recommender System Based on Local Random Walks and Spectral Methods
In this paper, we design recommender systems for weblogs based on the link structure among them. We propose algorithms based on refined random walks and spectral methods. First, w...
Zeinab Abbassi, Vahab S. Mirrokni
STOC
2002
ACM
149views Algorithms» more  STOC 2002»
14 years 8 months ago
The complexity of choosing an H-colouring (nearly) uniformly at random
Cooper, Dyer and Frieze studied the problem of sampling H-colourings (nearly) uniformly at random. Special cases of this problem include sampling colourings and independent sets a...
Leslie Ann Goldberg, Steven Kelk, Mike Paterson