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130
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ICCV
2003
IEEE
16 years 5 months ago
Boosting Chain Learning for Object Detection
A general classification framework, called boosting chain, is proposed for learning boosting cascade. In this framework, a "chain" structure is introduced to integrate h...
Rong Xiao, Long Zhu, HongJiang Zhang
115
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ICPR
2006
IEEE
16 years 4 months ago
A New Data Selection Principle for Semi-Supervised Incremental Learning
Current semi-supervised incremental learning approaches select unlabeled examples with predicted high confidence for model re-training. We show that for many applications this dat...
Alexander I. Rudnicky, Rong Zhang
155
Voted
ICML
2004
IEEE
16 years 4 months ago
Learning Bayesian network classifiers by maximizing conditional likelihood
Bayesian networks are a powerful probabilistic representation, and their use for classification has received considerable attention. However, they tend to perform poorly when lear...
Daniel Grossman, Pedro Domingos
126
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FLAIRS
2004
15 years 5 months ago
The Optimality of Naive Bayes
Naive Bayes is one of the most efficient and effective inductive learning algorithms for machine learning and data mining. Its competitive performance in classification is surpris...
Harry Zhang
124
Voted
CHI
2010
ACM
15 years 10 months ago
Learning basic dance choreographies with different augmented feedback modalities
We plan to evaluate different kinds of augmented feedback (tactile, video, sound) for learning basic dance choreographies. Therefore we develop a dance training system based on mo...
Dieter Drobny, Jan Borchers