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» Learning Models for Predicting Recognition Performance
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CVPR
2010
IEEE
15 years 8 months ago
Exploring Features in a Bayesian Framework for Material Recognition
We are interested in identifying the material category, e.g. glass, metal, fabric, plastic or wood, from a single image of a surface. Unlike other visual recognition tasks in comp...
Ce Liu, Lavanya Sharan, Edward Adelson, Ruth Rosen...
KDD
2002
ACM
136views Data Mining» more  KDD 2002»
16 years 9 days ago
Relational Markov models and their application to adaptive web navigation
Relational Markov models (RMMs) are a generalization of Markov models where states can be of different types, with each type described by a different set of variables. The domain ...
Corin R. Anderson, Pedro Domingos, Daniel S. Weld
CIKM
2009
Springer
15 years 6 months ago
Large margin transductive transfer learning
Recently there has been increasing interest in the problem of transfer learning, in which the typical assumption that training and testing data are drawn from identical distributi...
Brian Quanz, Jun Huan
MCS
2009
Springer
15 years 6 months ago
Selective Ensemble under Regularization Framework
An ensemble is generated by training multiple component learners for a same task and then combining them for predictions. It is known that when lots of trained learners are availab...
Nan Li, Zhi-Hua Zhou
ICASSP
2009
IEEE
15 years 6 months ago
Unsupervised equalization of Lombard effect for speech recognition in noisy adverse environment
When exposed to environmental noise, speakers adjust their speech production to maintain intelligible communication. This phenomenon, called Lombard effect (LE), is known to consi...
Hynek Boril, John H. L. Hansen