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IPSN
2004
Springer
14 years 28 days ago
Nonparametric belief propagation for self-calibration in sensor networks
Automatic self-calibration of ad-hoc sensor networks is a critical need for their use in military or civilian applications. In general, self-calibration involves the combination o...
Alexander T. Ihler, John W. Fisher III, Randolph L...
NN
2007
Springer
267views Neural Networks» more  NN 2007»
13 years 7 months ago
Modeling of gene regulatory networks with hybrid differential evolution and particle swarm optimization
In the last decade, recurrent neural networks (RNNs) have attracted more efforts in inferring genetic regulatory networks (GRNs), using time series gene expression data from micro...
Rui Xu, Ganesh K. Venayagamoorthy, Donald C. Wunsc...
JMLR
2006
389views more  JMLR 2006»
13 years 7 months ago
A Very Fast Learning Method for Neural Networks Based on Sensitivity Analysis
This paper introduces a learning method for two-layer feedforward neural networks based on sensitivity analysis, which uses a linear training algorithm for each of the two layers....
Enrique Castillo, Bertha Guijarro-Berdiñas,...
NOMS
2006
IEEE
169views Communications» more  NOMS 2006»
14 years 1 months ago
Real-Time Measurement of End-to-End Available Bandwidth using Kalman Filtering
—This paper presents a new method, BART (Bandwidth Available in Real-Time), for estimating the end-toend available bandwidth over a network path. It estimates bandwidth quasi-con...
Svante Ekelin, Martin Nilsson, Erik Hartikainen, A...
CSDA
2007
126views more  CSDA 2007»
13 years 7 months ago
A consistent nonparametric Bayesian procedure for estimating autoregressive conditional densities
This article proposes a Bayesian infinite mixture model for the estimation of the conditional density of an ergodic time series. A nonparametric prior on the conditional density ...
Yongqiang Tang, Subhashis Ghosal