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» A Minimax Method for Learning Functional Networks
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RAS
2000
161views more  RAS 2000»
13 years 7 months ago
Active object recognition by view integration and reinforcement learning
A mobile agent with the task to classify its sensor pattern has to cope with ambiguous information. Active recognition of three-dimensional objects involves the observer in a sear...
Lucas Paletta, Axel Pinz
ICASSP
2011
IEEE
12 years 11 months ago
Adaptive modelling with tunable RBF network using multi-innovation RLS algorithm assisted by swarm intelligence
— In this paper, we propose a new on-line learning algorithm for the non-linear system identification: the swarm intelligence aided multi-innovation recursive least squares (SIM...
Hao Chen, Yu Gong, Xia Hong
BMCBI
2008
138views more  BMCBI 2008»
13 years 7 months ago
Using neural networks and evolutionary information in decoy discrimination for protein tertiary structure prediction
Background: We present a novel method of protein fold decoy discrimination using machine learning, more specifically using neural networks. Here, decoy discrimination is represent...
Ching-Wai Tan, David T. Jones
GLOBECOM
2008
IEEE
14 years 1 months ago
Distributed Regression in Sensor Networks with a Reduced-Order Kernel Model
Abstract—Over the past few years, wireless sensor networks received tremendous attention for monitoring physical phenomena, such as the temperature field in a given region. Appl...
Paul Honeine, Mehdi Essoloh, Cédric Richard...
GECCO
2007
Springer
158views Optimization» more  GECCO 2007»
14 years 1 months ago
A novel generative encoding for exploiting neural network sensor and output geometry
A significant problem for evolving artificial neural networks is that the physical arrangement of sensors and effectors is invisible to the evolutionary algorithm. For example,...
David B. D'Ambrosio, Kenneth O. Stanley