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» Sampling from large graphs
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KDD
2008
ACM
165views Data Mining» more  KDD 2008»
16 years 3 days ago
Colibri: fast mining of large static and dynamic graphs
Low-rank approximations of the adjacency matrix of a graph are essential in finding patterns (such as communities) and detecting anomalies. Additionally, it is desirable to track ...
Hanghang Tong, Spiros Papadimitriou, Jimeng Sun, P...
MLG
2007
Springer
15 years 5 months ago
Inferring Vertex Properties from Topology in Large Networks
: Network topology not only tells about tightly-connected “communities,” but also gives cues on more subtle properties of the vertices. We introduce a simple probabilistic late...
Janne Sinkkonen, Janne Aukia, Samuel Kaski
BIRTHDAY
2005
Springer
15 years 1 months ago
From Graph Transformation to Software Engineering and Back
Software engineers usually represent problems and solutions aph-based notations at different levels of abstractions. These notations are often semi-formal, but the use of graph tr...
Luciano Baresi, Mauro Pezzè
BMCBI
2006
102views more  BMCBI 2006»
14 years 11 months ago
Microarray analysis distinguishes differential gene expression patterns from large and small colony Thymidine kinase mutants of
Background: The Thymidine kinase (Tk) mutants generated from the widely used L5178Y mouse lymphoma assay fall into two categories, small colony and large colony. Cells from the la...
Tao Han, Jianyong Wang, Weida Tong, Martha M. Moor...
CVPR
2007
IEEE
16 years 1 months ago
A Multi-Resolution Dynamic Model for Face Aging Simulation
In this paper we present a dynamic model for simulating face aging process. We adopt a high resolution grammatical face model[1] and augment it with age and hair features. This mo...
Jin-Li Suo, Feng Min, Song Chun Zhu, Shiguang Shan...