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IJCNN
2006
IEEE
15 years 4 months ago
Improving the Convergence of Backpropagation by Opposite Transfer Functions
—The backpropagation algorithm is a very popular approach to learning in feed-forward multi-layer perceptron networks. However, in many scenarios the time required to adequately ...
Mario Ventresca, Hamid R. Tizhoosh
ISNN
2005
Springer
15 years 3 months ago
FPGA Realization of a Radial Basis Function Based Nonlinear Channel Equalizer
In this paper we propose a radial basis function (RBF) neural network for nonlinear time-invariant channel equalizer. The RBF network model has a three-layer structure which is com...
Poyueh Chen, Hungming Tsai, ChengJian Lin, ChiYung...
ALT
2001
Springer
15 years 7 months ago
Learning of Boolean Functions Using Support Vector Machines
This paper concerns the design of a Support Vector Machine (SVM) appropriate for the learning of Boolean functions. This is motivated by the need of a more sophisticated algorithm ...
Ken Sadohara
WWW
2011
ACM
14 years 4 months ago
Learning to rank with multiple objective functions
We investigate the problem of learning to rank for document retrieval from the perspective of learning with multiple objective functions. We present solutions to two open problems...
Krysta Marie Svore, Maksims Volkovs, Christopher J...
ACL
1998
14 years 11 months ago
PAT-Trees with the Deletion Function as the Learning Device for Linguistic Patterns
In this study, a learning device based on the PATtree data structures was developed. The original PAT-trees were enhanced with the deletion function to emulate human learning comp...
Keh-Jiann Chen, Wen Tsuei, Lee-Feng Chien