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» Training Methods for Adaptive Boosting of Neural Networks
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ESANN
2000
14 years 11 months ago
Local input-output stability of recurrent networks with time-varying weights
Abstract. We present local conditions for input-output stability of recurrent neural networks with time-varying parameters introduced for instance by noise or on-line adaptation. T...
Jochen J. Steil
ICIP
2003
IEEE
15 years 11 months ago
Image compression with on-line and off-line learning
Images typically contain smooth regions, which are easily compressed by linear transforms, and high activity regions (edges, textures), which are harder to compress. To compress t...
Patrice Y. Simard, Christopher J. C. Burges, David...
BMCBI
2005
122views more  BMCBI 2005»
14 years 9 months ago
A neural strategy for the inference of SH3 domain-peptide interaction specificity
Background: The SH3 domain family is one of the most representative and widely studied cases of so-called Peptide Recognition Modules (PRM). The polyproline II motif PxxP that gen...
Enrico Ferraro, Allegra Via, Gabriele Ausiello, Ma...
FOCI
2007
IEEE
15 years 4 months ago
Opposite Transfer Functions and Backpropagation Through Time
— Backpropagation through time is a very popular discrete-time recurrent neural network training algorithm. However, the computational time associated with the learning process t...
Mario Ventresca, Hamid R. Tizhoosh
65
Voted
IJCNN
2007
IEEE
15 years 4 months ago
A Functional Link Network With Ordered Basis Functions
—A procedure is presented for selecting and ordering the polynomial basis functions in the functional link net (FLN). This procedure, based upon a modified Gram Schmidt orthonorm...
Saurabh Sureka, Michael T. Manry