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» Constructive Neural Network Learning Algorithms
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GECCO
2009
Springer
135views Optimization» more  GECCO 2009»
14 years 2 months ago
Neuroevolutionary reinforcement learning for generalized helicopter control
Helicopter hovering is an important challenge problem in the field of reinforcement learning. This paper considers several neuroevolutionary approaches to discovering robust cont...
Rogier Koppejan, Shimon Whiteson
UAI
2003
13 years 9 months ago
Large-Sample Learning of Bayesian Networks is NP-Hard
In this paper, we provide new complexity results for algorithms that learn discrete-variable Bayesian networks from data. Our results apply whenever the learning algorithm uses a ...
David Maxwell Chickering, Christopher Meek, David ...
ICMLA
2008
13 years 9 months ago
Tumor Targeting for Lung Cancer Radiotherapy Using Machine Learning Techniques
Accurate lung tumor targeting in real time plays a fundamental role in image-guide radiotherapy of lung cancers. Precise tumor targeting is required for both respiratory gating an...
Tong Lin, Laura Cervino, Xiaoli Tang, Nuno Vasconc...
BMCBI
2008
141views more  BMCBI 2008»
13 years 7 months ago
Functional discrimination of membrane proteins using machine learning techniques
Background: Discriminating membrane proteins based on their functions is an important task in genome annotation. In this work, we have analyzed the characteristic features of amin...
M. Michael Gromiha, Yukimitsu Yabuki
NECO
2008
170views more  NECO 2008»
13 years 7 months ago
Representational Power of Restricted Boltzmann Machines and Deep Belief Networks
Deep Belief Networks (DBN) are generative neural network models with many layers of hidden explanatory factors, recently introduced by Hinton et al., along with a greedy layer-wis...
Nicolas Le Roux, Yoshua Bengio