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GECCO
2007
Springer
158views Optimization» more  GECCO 2007»
15 years 6 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
MLMI
2007
Springer
15 years 6 months ago
Binaural Speech Separation Using Recurrent Timing Neural Networks for Joint F0-Localisation Estimation
A speech separation system is described in which sources are represented in a joint interaural time difference-fundamental frequency (ITD-F0) cue space. Traditionally, recurrent t...
Stuart N. Wrigley, Guy J. Brown
ESWA
2008
169views more  ESWA 2008»
14 years 11 months ago
Predicting opponent's moves in electronic negotiations using neural networks
Electronic negotiation experiments provide a rich source of information about relationships between the negotiators, their individual actions, and the negotiation dynami...
Réal Carbonneau, Gregory E. Kersten, Rustam...
ICPR
2006
IEEE
16 years 29 days ago
Rotation-Invariant Neoperceptron
Approaches based on local features and descriptors are increasingly used for the task of object recognition due to their robustness with regard to occlusions and geometrical defor...
Beat Fasel, Daniel Gatica-Perez
ICANN
2003
Springer
15 years 5 months ago
Optimal Hebbian Learning: A Probabilistic Point of View
Many activity dependent learning rules have been proposed in order to model long-term potentiation (LTP). Our aim is to derive a spike time dependent learning rule from a probabili...
Jean-Pascal Pfister, David Barber, Wulfram Gerstne...