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» Learning to generalize for complex selection tasks
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141
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GECCO
2004
Springer
103views Optimization» more  GECCO 2004»
15 years 9 months ago
Training Neural Networks with GA Hybrid Algorithms
Abstract. Training neural networks is a complex task of great importance in the supervised learning field of research. In this work we tackle this problem with five algorithms, a...
Enrique Alba, J. Francisco Chicano
138
Voted
PAMI
2007
193views more  PAMI 2007»
15 years 3 months ago
Robust Object Recognition with Cortex-Like Mechanisms
—We introduce a new general framework for the recognition of complex visual scenes, which is motivated by biology: We describe a hierarchical system that closely follows the orga...
Thomas Serre, Lior Wolf, Stanley M. Bileschi, Maxi...
194
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Publication
151views
13 years 7 months ago
Can faces verify blood-relations?
Humans can verify unknown parent-offspring and sibling pairs over unrelated subject pairs. A computational scheme to accomplish the task robustly, in the presence of challenges due...
Gowri Somanath, Chandra Kambhamettu
118
Voted
CVPR
2008
IEEE
16 years 5 months ago
Discovering class specific composite features through discriminative sampling with Swendsen-Wang Cut
This paper proposes a novel approach to discover a set of class specific "composite features" as the feature pool for the detection and classification of complex objects...
Feng Han, Ying Shan, Harpreet S. Sawhney, Rakesh K...
148
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CIKM
2009
Springer
15 years 10 months ago
L2 norm regularized feature kernel regression for graph data
Features in many real world applications such as Cheminformatics, Bioinformatics and Information Retrieval have complex internal structure. For example, frequent patterns mined fr...
Hongliang Fei, Jun Huan