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» Network Probabilistic Connectivity: Optimal Structures
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GECCO
2003
Springer
153views Optimization» more  GECCO 2003»
15 years 4 months ago
SEPA: Structure Evolution and Parameter Adaptation in Feed-Forward Neural Networks
Abstract. In developing algorithms that dynamically changes the structure and weights of ANN (Artificial Neural Networks), there must be a proper balance between network complexit...
Paulito P. Palmes, Taichi Hayasaka, Shiro Usui
IJON
2006
112views more  IJON 2006»
14 years 11 months ago
Palmprint recognition using FastICA algorithm and radial basis probabilistic neural network
This paper proposes a novel and successful method for recognizing palmprint based on radial basis probabilistic neural network (RBPNN) proposed by us. The RBPNN is trained by the ...
Li Shang, De-Shuang Huang, Ji-Xiang Du, Chun-Hou Z...
TSMC
2002
98views more  TSMC 2002»
14 years 11 months ago
The STAR automaton: expediency and optimality properties
Abstract--We present the STack ARchitecture (STAR) automaton. It is a fixed structure, multiaction, reward-penalty learning automaton, characterized by a star-shaped state transiti...
Anastasios A. Economides, Athanasios Kehagias
153
Voted
CVPR
2011
IEEE
14 years 9 months ago
Sparsity-based Image Denoising via Dictionary Learning and Structural Clustering
Where does the sparsity in image signals come from? Local and nonlocal image models have supplied complementary views toward the regularity in natural images the former attempts t...
Weisheng Dong, Xin Li
83
Voted
GECCO
2004
Springer
15 years 5 months ago
Shortcomings with Tree-Structured Edge Encodings for Neural Networks
In evolutionary algorithms a common method for encoding neural networks is to use a tree-structured assembly procedure for constructing them. Since node operators have difficulties...
Gregory Hornby