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AI
2002
Springer
15 years 3 months ago
Learning Bayesian networks from data: An information-theory based approach
This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...
AVI
2010
15 years 4 months ago
Advanced visual analytics interfaces
Advanced visual interfaces, like the ones found in informaualization, intend to offer a view on abstract data spaces to enable users to make sense of them. By mapping data to visu...
Daniel A. Keim, Peter Bak, Enrico Bertini, Daniela...
147
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KDD
2009
ACM
203views Data Mining» more  KDD 2009»
16 years 3 months ago
Characterizing individual communication patterns
The increasing availability of electronic communication data, such as that arising from e-mail exchange, presents social and information scientists with new possibilities for char...
R. Dean Malmgren, Jake M. Hofman, Luis A. N. Amara...
129
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TSP
2010
14 years 10 months ago
Gaussian multiresolution models: exploiting sparse Markov and covariance structure
We consider the problem of learning Gaussian multiresolution (MR) models in which data are only available at the finest scale and the coarser, hidden variables serve both to captu...
Myung Jin Choi, Venkat Chandrasekaran, Alan S. Wil...
ICCV
2007
IEEE
16 years 5 months ago
Conditional State Space Models for Discriminative Motion Estimation
We consider the problem of predicting a sequence of real-valued multivariate states from a given measurement sequence. Its typical application in computer vision is the task of mo...
Minyoung Kim, Vladimir Pavlovic