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» Explaining inferences in Bayesian networks
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IEAAIE
2007
Springer
14 years 1 months ago
Generating Cartoon-Style Summary of Daily Life with Multimedia Mobile Devices
Mobile devices are treasure boxes of personal information containing user’s context, personal schedule, diary, short messages, photos, and videos. Also, user’s usage informatio...
Sung-Bae Cho, Kyung-Joong Kim, Keum-Sung Hwang
AICCSA
2006
IEEE
133views Hardware» more  AICCSA 2006»
14 years 1 months ago
Learning acyclic rules based on Chaining Genetic Programming
Multi-class problem is the class of problems having more than one classes in the data set. Bayesian Network (BN) is a well-known algorithm handling the multi-class problem and is ...
Wing-Ho Shum, Kwong-Sak Leung, Man Leung Wong
IJAR
2010
97views more  IJAR 2010»
13 years 6 months ago
Parameter estimation and model selection for mixtures of truncated exponentials
Bayesian networks with mixtures of truncated exponentials (MTEs) support efficient inference algorithms and provide a flexible way of modeling hybrid domains (domains containing ...
Helge Langseth, Thomas D. Nielsen, Rafael Rum&iacu...
BMVC
2010
13 years 5 months ago
Label propagation in complex video sequences using semi-supervised learning
We propose a novel directed graphical model for label propagation in lengthy and complex video sequences. Given hand-labelled start and end frames of a video sequence, a variation...
Ignas Budvytis, Vijay Badrinarayanan, Roberto Cipo...
WEBI
2010
Springer
13 years 5 months ago
An Approach to Model and Predict the Popularity of Online Contents with Explanatory Factors
In this paper, we propose a methodology to predict the popularity of online contents. More precisely, rather than trying to infer the popularity of a content itself, we infer the l...
Jong Gun Lee, Sue Moon, Kavé Salamatian