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NIPS
1993
13 years 9 months ago
Structural and Behavioral Evolution of Recurrent Networks
This paper introduces GNARL, an evolutionary program which induces recurrent neural networks that are structurally unconstrained. In contrast to constructive and destructive algor...
Gregory M. Saunders, Peter J. Angeline, Jordan B. ...
NCA
2010
IEEE
13 years 6 months ago
Genetic algorithm-based training for semi-supervised SVM
The Support Vector Machine (SVM) is an interesting classifier with excellent power of generalization. In this paper, we consider applying the SVM to semi-supervised learning. We p...
Mathias M. Adankon, Mohamed Cheriet
MOBIHOC
2008
ACM
14 years 8 months ago
Efficient binary schemes for training heterogeneous sensor and actor networks
Sensor networks are expected to evolve into long-lived, autonomous networked systems whose main mission is to provide in-situ users ? called actors ? with real-time information in...
Ferruccio Barsi, Alfredo Navarra, Maria Cristina P...
COCOA
2007
Springer
14 years 2 months ago
A New Dynamic Programming Algorithm for Multiple Sequence Alignment
Abstract. Multiple sequence alignment (MSA) is one of the most basic and central tasks for many studies in modern biology. In this paper, we present a new progressive alignment alg...
Jean-Michel Richer, Vincent Derrien, Jin-Kao Hao
ISCI
2008
95views more  ISCI 2008»
13 years 8 months ago
Modified constrained learning algorithms incorporating additional functional constraints into neural networks
In this paper, two modified constrained learning algorithms are proposed to obtain better generalization performance and faster convergence rate. The additional cost terms of the ...
Fei Han, Qing-Hua Ling, De-Shuang Huang