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ISNN
2010
Springer
13 years 5 months ago
Particle Swarm Optimization Based Learning Method for Process Neural Networks
Abstract. This paper proposes a new learning method for process neural networks (PNNs) based on the Gaussian mixture functions and particle swarm optimization (PSO), called PSO-LM....
Kun Liu, Ying Tan, Xingui He
NIPS
1998
13 years 8 months ago
Modeling Surround Suppression in V1 Neurons with a Statistically Derived Normalization Model
We examine the statistics of natural monochromatic images decomposed using a multi-scale wavelet basis. Although the coefficients of this representation are nearly decorrelated, t...
Eero P. Simoncelli, Odelia Schwartz
NPL
2006
172views more  NPL 2006»
13 years 6 months ago
Adapting RBF Neural Networks to Multi-Instance Learning
In multi-instance learning, the training examples are bags composed of instances without labels, and the task is to predict the labels of unseen bags through analyzing the training...
Min-Ling Zhang, Zhi-Hua Zhou
SAC
2010
ACM
14 years 1 months ago
A wavelet-based sampling algorithm for wireless sensor networks applications
This work proposes and evaluates a sampling algorithm based on wavelet transforms with Coiflets basis to reduce the data sensed in wireless sensor networks applications. The Coiï...
André L. L. de Aquino, Ricardo A. R. Olivei...
PKDD
2009
Springer
107views Data Mining» more  PKDD 2009»
14 years 1 months ago
Neural Networks for State Evaluation in General Game Playing
Unlike traditional game playing, General Game Playing is concerned with agents capable of playing classes of games. Given the rules of an unknown game, the agent is supposed to pla...
Daniel Michulke, Michael Thielscher