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» Spectral Generative Models for Graphs
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SDM
2004
SIAM
229views Data Mining» more  SDM 2004»
13 years 9 months ago
R-MAT: A Recursive Model for Graph Mining
How does a `normal' computer (or social) network look like? How can we spot `abnormal' sub-networks in the Internet, or web graph? The answer to such questions is vital ...
Deepayan Chakrabarti, Yiping Zhan, Christos Falout...
ESANN
2007
13 years 10 months ago
Learning topology of a labeled data set with the supervised generative gaussian graph
Abstract. Discovering the topology of a set of labeled data in a Euclidian space can help to design better decision systems. In this work, we propose a supervised generative model ...
Pierre Gaillard, Michaël Aupetit, Géra...
NIPS
2003
13 years 9 months ago
Denoising and Untangling Graphs Using Degree Priors
This paper addresses the problem of untangling hidden graphs from a set of noisy detections of undirected edges. We present a model of the generation of the observed graph that in...
Quaid Morris, Brendan J. Frey
ICML
2003
IEEE
14 years 9 months ago
Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions
An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, wit...
Xiaojin Zhu, Zoubin Ghahramani, John D. Lafferty
ASUNAM
2011
IEEE
12 years 8 months ago
Content-based Modeling and Prediction of Information Dissemination
—Social and communication networks across the world generate vast amounts of graph-like data each day. The modeling and prediction of how these communication structures evolve ca...
Kathy Macropol, Ambuj K. Singh