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» Approximating the Number of Network Motifs
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TNN
1998
111views more  TNN 1998»
14 years 9 months ago
Asymptotic distributions associated to Oja's learning equation for neural networks
— In this paper, we perform a complete asymptotic performance analysis of the stochastic approximation algorithm (denoted subspace network learning algorithm) derived from Oja’...
Jean Pierre Delmas, Jean-Francois Cardos
IJCNN
2006
IEEE
15 years 3 months ago
Studies on the Memory Capacity and Robustness of Chaotic Dynamic Neural Networks
- A dynamical neural model that is strongly biologically motivated is applied to learning and retrieving binary patterns. This neural network, known as Freeman’s Ksets, is traine...
Igor Beliaev, Robert Kozma
JMLR
2010
143views more  JMLR 2010»
14 years 4 months ago
Incremental Sigmoid Belief Networks for Grammar Learning
We propose a class of Bayesian networks appropriate for structured prediction problems where the Bayesian network's model structure is a function of the predicted output stru...
James Henderson, Ivan Titov
TON
2002
85views more  TON 2002»
14 years 9 months ago
The impact of point-to-multipoint traffic concentration on multirate networks design
We consider the problem of multirate network design with point-to-multipoint communications. We give a mathematical formulation for this problem. Using approximations, we show that...
Aref Meddeb, André Girard, Catherine Rosenb...
GLOBECOM
2006
IEEE
15 years 3 months ago
Interdomain RWA Based on Stochastic Estimation Methods and Adaptive Filtering for Optical Networks
Abstract- This paper presents a RWA strategy based on the stochastic estimation of the Effective Number of Available Wavelengths (ENAW) along interdomain paths. We propose an appro...
Marcelo Yannuzzi, Xavier Masip-Bruin, Sergio S&aac...