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IJCAI
1989
13 years 8 months ago
Generation, Local Receptive Fields and Global Convergence Improve Perceptual Learning in Connectionist Networks
This paper presents and compares results for three types of connectionist networks on perceptual learning tasks: [A] Multi-layered converging networks of neuron-like units, with e...
Vasant Honavar, Leonard Uhr
NLPRS
2001
Springer
14 years 4 days ago
Named Entity Recognition using Machine Learning Methods and Pattern-Selection Rules
Named Entity recognition, as a task of providing important semantic information, is a critical first step in Information Extraction and QuestionAnswering system. This paper propos...
Choong-Nyoung Seon, Youngjoong Ko, Jeong-Seok Kim,...
PR
2007
118views more  PR 2007»
13 years 7 months ago
A cooperative constructive method for neural networks for pattern recognition
In this paper, we propose a new constructive method, based on cooperative coevolution, for designing automatically the structure of a neural network for classification. Our appro...
Nicolás García-Pedrajas, Domingo Ort...
KES
1998
Springer
13 years 12 months ago
Hidden partitioning of a visual feedback-based neuro-controller
Robotic controllers take advantage from neural network learning capabilities as long as the dimensionality of the problem is kept moderate. This paper explores the possibilities of...
Jean-Philippe Urban, Jean-Luc Buessler, Julien Gre...
CVPR
1997
IEEE
14 years 9 months ago
Global Training of Document Processing Systems Using Graph Transformer Networks
We propose a new machine learning paradigm called Graph Transformer Networks that extends the applicability of gradient-based learning algorithms to systems composed of modules th...
Léon Bottou, Yoshua Bengio, Yann LeCun