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» A Graph Theoretical Approach to Network Encoding Complexity
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ICML
2003
IEEE
16 years 3 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
WWW
2011
ACM
14 years 10 months ago
Estimating sizes of social networks via biased sampling
Online social networks have become very popular in recent years and their number of users is already measured in many hundreds of millions. For various commercial and sociological...
Liran Katzir, Edo Liberty, Oren Somekh
ICPR
2002
IEEE
16 years 4 months ago
Relational Graph Labelling Using Learning Techniques and Markov Random Fields
This paper introduces an approach for handling complex labelling problems driven by local constraints. The purpose is illustrated by two applications: detection of the road networ...
Denis Rivière, Jean-Francois Mangin, Jean-M...
WWW
2006
ACM
16 years 3 months ago
Communities from seed sets
Expanding a seed set into a larger community is a common procedure in link-based analysis. We show how to adapt recent results from theoretical computer science to expand a seed s...
Reid Andersen, Kevin J. Lang
IJCINI
2007
125views more  IJCINI 2007»
15 years 2 months ago
A Unified Approach To Fractal Dimensions
The Cognitive Processes of Abstraction and Formal Inferences J. A. Anderson: A Brain-Like Computer for Cognitive Software Applications: the Resatz Brain Project L. Flax: Cognitive ...
Witold Kinsner