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ICML
2005
IEEE
16 years 2 months ago
Efficient discriminative learning of Bayesian network classifier via boosted augmented naive Bayes
The use of Bayesian networks for classification problems has received significant recent attention. Although computationally efficient, the standard maximum likelihood learning me...
Yushi Jing, Vladimir Pavlovic, James M. Rehg
ACL
2006
15 years 3 months ago
Learning to Predict Case Markers in Japanese
Japanese case markers, which indicate the grammatical relation of the complement NP to the predicate, often pose challenges to the generation of Japanese text, be it done by a for...
Hisami Suzuki, Kristina Toutanova
ICML
2006
IEEE
16 years 2 months ago
Simpler knowledge-based support vector machines
If appropriately used, prior knowledge can significantly improve the predictive accuracy of learning algorithms or reduce the amount of training data needed. In this paper we intr...
Quoc V. Le, Alex J. Smola, Thomas Gärtner
AAAI
2007
15 years 4 months ago
Learning to Solve QBF
We present a novel approach to solving Quantified Boolean Formulas (QBF) that combines a search-based QBF solver with machine learning techniques. We show how classification met...
Horst Samulowitz, Roland Memisevic
BMCBI
2007
113views more  BMCBI 2007»
15 years 1 months ago
Learning biophysically-motivated parameters for alpha helix prediction
Background: Our goal is to develop a state-of-the-art protein secondary structure predictor, with an intuitive and biophysically-motivated energy model. We treat structure predict...
Blaise Gassend, Charles W. O'Donnell, William Thie...