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» Modeling Classification and Inference Learning
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ECCV
2008
Springer
14 years 10 months ago
Constrained Maximum Likelihood Learning of Bayesian Networks for Facial Action Recognition
Probabilistic graphical models such as Bayesian Networks have been increasingly applied to many computer vision problems. Accuracy of inferences in such models depends on the quali...
Cassio Polpo de Campos, Yan Tong, Qiang Ji
NIPS
2004
13 years 9 months ago
Learning Efficient Auditory Codes Using Spikes Predicts Cochlear Filters
The representation of acoustic signals at the cochlear nerve must serve a wide range of auditory tasks that require exquisite sensitivity in both time and frequency. Lewicki (2002...
Evan C. Smith, Michael S. Lewicki
ICMLA
2008
13 years 9 months ago
Predicting Algorithm Accuracy with a Small Set of Effective Meta-Features
We revisit 26 meta-features typically used in the context of meta-learning for model selection. Using visual analysis and computational complexity considerations, we find 4 meta-f...
Jun Won Lee, Christophe G. Giraud-Carrier
CORR
2008
Springer
101views Education» more  CORR 2008»
13 years 8 months ago
Belief decision support and reject for textured images characterization
: The textured images' classification assumes to consider the images in terms of area with the same texture. In uncertain environment, it could be better to take an imprecise ...
Arnaud Martin
WWW
2006
ACM
14 years 9 months ago
Large-scale text categorization by batch mode active learning
Large-scale text categorization is an important research topic for Web data mining. One of the challenges in large-scale text categorization is how to reduce the amount of human e...
Steven C. H. Hoi, Rong Jin, Michael R. Lyu