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» Exploiting Data Missingness in Bayesian Network Modeling
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161
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PAMI
2011
14 years 9 months ago
Greedy Learning of Binary Latent Trees
—Inferring latent structures from observations helps to model and possibly also understand underlying data generating processes. A rich class of latent structures are the latent ...
Stefan Harmeling, Christopher K. I. Williams
103
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IJAR
2008
167views more  IJAR 2008»
15 years 2 months ago
Approximate algorithms for credal networks with binary variables
This paper presents a family of algorithms for approximate inference in credal networks (that is, models based on directed acyclic graphs and set-valued probabilities) that contai...
Jaime Shinsuke Ide, Fabio Gagliardi Cozman
125
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AAAI
2004
15 years 4 months ago
High-Level Goal Recognition in a Wireless LAN
Plan recognition has traditionally been developed for logically encoded application domains with a focus on logical reasoning. In this paper, we present an integrated plan-recogni...
Jie Yin, Xiaoyong Chai, Qiang Yang
143
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BMCBI
2010
143views more  BMCBI 2010»
15 years 2 months ago
Learning gene regulatory networks from only positive and unlabeled data
Background: Recently, supervised learning methods have been exploited to reconstruct gene regulatory networks from gene expression data. The reconstruction of a network is modeled...
Luigi Cerulo, Charles Elkan, Michele Ceccarelli
103
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MASS
2010
15 years 16 days ago
Geography-aware active data dissemination in mobile social networks
Abstract--In mobile social networks (MSNets), data dissemination is an important topic, which has not been widely investigated yet. Active data dissemination is a networking paradi...
Jialu Fan, Yuan Du, Wei Gao, Jiming Chen, Youxian ...