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ICML
2004
IEEE
16 years 7 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
ICML
2003
IEEE
16 years 7 months ago
Tractable Bayesian Learning of Tree Augmented Naive Bayes Models
Bayesian classifiers such as Naive Bayes or Tree Augmented Naive Bayes (TAN) have shown excellent performance given their simplicity and heavy underlying independence assumptions....
Jesús Cerquides, Ramon López de M&aa...
COLCOM
2008
IEEE
16 years 18 days ago
Learning Models of the Negotiation Partner in Spatio-temporal Collaboration
Abstract. We describe an approach for learning the model of the opponent in spatio-temporal negotiation. We use the Children in the Rectangular Forest canonical problem as an examp...
Yi Luo, Ladislau Bölöni
ICASSP
2008
IEEE
16 years 17 days ago
Improving Spoken Language Understanding with information retrieval and active learning methods
In the context of deployed spoken dialogue telecom services, we introduce a preprocessor called Fiction into the Spoken Language Understanding (SLU) component. It acts as an inter...
Isabelle Jars, Franck Panaget
137
Voted
COLT
2007
Springer
16 years 9 days ago
Learning Permutations with Exponential Weights
We give an algorithm for the on-line learning of permutations. The algorithm maintains its uncertainty about the target permutation as a doubly stochastic weight matrix, and makes...
David P. Helmbold, Manfred K. Warmuth