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» Exploiting Data Missingness in Bayesian Network Modeling
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PAMI
2011
14 years 6 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
IJAR
2008
167views more  IJAR 2008»
14 years 11 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
AAAI
2004
15 years 13 days 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
BMCBI
2010
143views more  BMCBI 2010»
14 years 11 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
79
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MASS
2010
14 years 9 months 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 ...