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AAAI
2008
15 years 9 months ago
Bounding the False Discovery Rate in Local Bayesian Network Learning
Modern Bayesian Network learning algorithms are timeefficient, scalable and produce high-quality models; these algorithms feature prominently in decision support model development...
Ioannis Tsamardinos, Laura E. Brown
FLAIRS
2008
15 years 9 months ago
Learning Dynamic Naive Bayesian Classifiers
Hidden Markov models are a powerful technique to model and classify temporal sequences, such as in speech and gesture recognition. However, defining these models is still an art: ...
Miriam Martínez, Luis Enrique Sucar
ECAI
2008
Springer
15 years 8 months ago
Reinforcement Learning with Classifier Selection for Focused Crawling
Focused crawlers are programs that wander in the Web, using its graph structure, and gather pages that belong to a specific topic. The most critical task in Focused Crawling is the...
Ioannis Partalas, Georgios Paliouras, Ioannis P. V...
HIS
2008
15 years 8 months ago
The Hybrid Integration of Perceptual Symbol Systems and Interactive Reinforcement Learning
In order to produce robots which can interact more effectively with humans we propose that it is necessary for their cognitive processes to be grounded in the same perceptual elem...
Michael John Knowles, Stefan Wermter
EACL
2006
ACL Anthology
15 years 8 months ago
Using Reinforcement Learning to Build a Better Model of Dialogue State
Given the growing complexity of tasks that spoken dialogue systems are trying to handle, Reinforcement Learning (RL) has been increasingly used as a way of automatically learning ...
Joel R. Tetreault, Diane J. Litman