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» Fast Approximate Graph Partitioning Algorithms
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KDD
2005
ACM
162views Data Mining» more  KDD 2005»
14 years 8 months ago
Discovering frequent topological structures from graph datasets
The problem of finding frequent patterns from graph-based datasets is an important one that finds applications in drug discovery, protein structure analysis, XML querying, and soc...
Ruoming Jin, Chao Wang, Dmitrii Polshakov, Sriniva...
FOCS
2009
IEEE
14 years 2 months ago
Faster Generation of Random Spanning Trees
In this paper, we set forth a new algorithm for generating approximately uniformly random spanning trees in undirected graphs. We show how to sample from a distribution that is wi...
Jonathan A. Kelner, Aleksander Madry
CIAC
2006
Springer
103views Algorithms» more  CIAC 2006»
13 years 11 months ago
Provisioning a Virtual Private Network Under the Presence of Non-communicating Groups
Virtual private network design in the hose model deals with the reservation of capacities in a weighted graph such that the terminals in this network can communicate with one anoth...
Friedrich Eisenbrand, Edda Happ
NIPS
2008
13 years 9 months ago
Regularized Co-Clustering with Dual Supervision
By attempting to simultaneously partition both the rows (examples) and columns (features) of a data matrix, Co-clustering algorithms often demonstrate surprisingly impressive perf...
Vikas Sindhwani, Jianying Hu, Aleksandra Mojsilovi...
TIP
2008
133views more  TIP 2008»
13 years 7 months ago
A Recursive Model-Reduction Method for Approximate Inference in Gaussian Markov Random Fields
This paper presents recursive cavity modeling--a principled, tractable approach to approximate, near-optimal inference for large Gauss-Markov random fields. The main idea is to su...
Jason K. Johnson, Alan S. Willsky