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PKDD
2010
Springer
129views Data Mining» more  PKDD 2010»
15 years 5 months ago
Smarter Sampling in Model-Based Bayesian Reinforcement Learning
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
Pablo Samuel Castro, Doina Precup
PR
2010
147views more  PR 2010»
15 years 5 months ago
Minimum classification error learning for sequential data in the wavelet domain
Wavelet analysis has found widespread use in signal processing and many classification tasks. Nevertheless, its use in dynamic pattern recognition have been much more restricted ...
D. Tomassi, Diego H. Milone, L. Forzani
175
Voted
ACL
2010
15 years 4 months ago
An Active Learning Approach to Finding Related Terms
We present a novel system that helps nonexperts find sets of similar words. The user begins by specifying one or more seed words. The system then iteratively suggests a series of ...
David Vickrey, Oscar Kipersztok, Daphne Koller
ICTAI
2010
IEEE
15 years 4 months ago
Combining Mixed Integer Programming and Supervised Learning for Fast Re-planning
We introduce a new plan repair method for problems cast as Mixed Integer Programs. In order to tackle the inherent complexity of these NP-hard problems, our approach relies on the ...
Emmanuel Rachelson, Ala Ben Abbes, Sebastien Dieme...
COLING
2010
15 years 1 months ago
A Comparison of Models for Cost-Sensitive Active Learning
Active Learning (AL) is a selective sampling strategy which has been shown to be particularly cost-efficient by drastically reducing the amount of training data to be manually ann...
Katrin Tomanek, Udo Hahn