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» A geometric view on learning Bayesian network structures
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WWW
2010
ACM
15 years 4 months ago
Sampling community structure
We propose a novel method, based on concepts from expander graphs, to sample communities in networks. We show that our sampling method, unlike previous techniques, produces subgra...
Arun S. Maiya, Tanya Y. Berger-Wolf
ICANN
2010
Springer
14 years 10 months ago
A Learned Saliency Predictor for Dynamic Natural Scenes
Abstract. We investigate the extent to which eye movements in natural dynamic scenes can be predicted with a simple model of bottom-up saliency, which learns on different visual re...
Eleonora Vig, Michael Dorr, Thomas Martinetz, Erha...
BMCBI
2008
174views more  BMCBI 2008»
14 years 9 months ago
Evolutionary approaches for the reverse-engineering of gene regulatory networks: A study on a biologically realistic dataset
Background: Inferring gene regulatory networks from data requires the development of algorithms devoted to structure extraction. When only static data are available, gene interact...
Cédric Auliac, Vincent Frouin, Xavier Gidro...
JCIT
2008
104views more  JCIT 2008»
14 years 9 months ago
Research and Design on Personalized Learning System Based on Mobile Agent
In view of students' individual difference in the learning process, in this paper we propose a personalized learning system, to which intelligent Agent technique and case-bas...
Yang He-biao, Chen Yu-kun, Wang Jue, Liu Zhi-hong
ML
2006
ACM
122views Machine Learning» more  ML 2006»
14 years 9 months ago
PRL: A probabilistic relational language
In this paper, we describe the syntax and semantics for a probabilistic relational language (PRL). PRL is a recasting of recent work in Probabilistic Relational Models (PRMs) into ...
Lise Getoor, John Grant