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CSL
2010
Springer
15 years 6 months ago
Evaluation of a hierarchical reinforcement learning spoken dialogue system
We describe an evaluation of spoken dialogue strategies designed using hierarchical reinforcement learning agents. The dialogue strategies were learnt in a simulated environment a...
Heriberto Cuayáhuitl, Steve Renals, Oliver ...
167
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BMCBI
2007
113views more  BMCBI 2007»
15 years 6 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...
DATAMINE
2002
125views more  DATAMINE 2002»
15 years 6 months ago
High-Performance Commercial Data Mining: A Multistrategy Machine Learning Application
We present an application of inductive concept learning and interactive visualization techniques to a large-scale commercial data mining project. This paper focuses on design and c...
William H. Hsu, Michael Welge, Thomas Redman, Davi...
NECO
2007
87views more  NECO 2007»
15 years 5 months ago
Reinforcement Learning State Estimator
cal networks in the learning of abstract and effector-specific representations of motor sequences. Neuroimage. 32, 714-727. (Neuroimage Editor’s Choice Award, 2006) Daw, N. D. Do...
Jun Morimoto, Kenji Doya
ICRA
2010
IEEE
142views Robotics» more  ICRA 2010»
15 years 4 months ago
Learning and planning high-dimensional physical trajectories via structured Lagrangians
— We consider the problem of finding sufficiently simple models of high-dimensional physical systems that are consistent with observed trajectories, and using these models to s...
Paul Vernaza, Daniel D. Lee, Seung-Joon Yi