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» Training Neural Networks with GA Hybrid Algorithms
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GECCO
2005
Springer
141views Optimization» more  GECCO 2005»
14 years 1 months ago
Constructing good learners using evolved pattern generators
Self-organization of brain areas in animals begins prenatally, evidently driven by spontaneously generated internal patterns. The neural structures continue to develop postnatally...
Vinod K. Valsalam, James A. Bednar, Risto Miikkula...
ML
1998
ACM
153views Machine Learning» more  ML 1998»
13 years 8 months ago
Bayesian Landmark Learning for Mobile Robot Localization
To operate successfully in indoor environments, mobile robots must be able to localize themselves. Most current localization algorithms lack flexibility, autonomy, and often optim...
Sebastian Thrun
GECCO
2008
Springer
110views Optimization» more  GECCO 2008»
13 years 9 months ago
Evolving stable behavior in a spino-neuromuscular system model
This paper demonstrates the effectiveness of genetic algorithms in training stable behavior in a model of the spinoneuromuscular system (SNMS). In particular, we test the stabili...
Stanley Phillips Gotshall, Terry Soule
ICIP
2007
IEEE
14 years 10 months ago
Iterative Blind Image Motion Deblurring via Learning a No-Reference Image Quality Measure
In this paper, we propose a learning-based image restoration algorithm for restoring images degraded by uniform motion blurs. The motion blur parameters are first approximately es...
Wen-Hao Lee, Shang-Hong Lai, Chia-Lun Chen
NN
1998
Springer
177views Neural Networks» more  NN 1998»
13 years 8 months ago
Soft vector quantization and the EM algorithm
The relation between hard c-means (HCM), fuzzy c-means (FCM), fuzzy learning vector quantization (FLVQ), soft competition scheme (SCS) of Yair et al. (1992) and probabilistic Gaus...
Ethem Alpaydin