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H N Mhaskar

Showing results (1-10 of 12) with videos related to

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Neural Networks : the Official Journal of the International Neural Network Society|August 18, 2004
When is approximation by Gaussian networks necessarily a linear process?H N Mhaskar
Neural Networks : the Official Journal of the International Neural Network Society|September 14, 2020
A direct approach for function approximation on data defined manifoldsH N Mhaskar
Neural Networks : the Official Journal of the International Neural Network Society|February 15, 2011
A generalized diffusion frame for parsimonious representation of functions on data defined manifoldsH N Mhaskar
Neural Networks : the Official Journal of the International Neural Network Society|December 24, 2019
Dimension independent bounds for general shallow networksH N Mhaskar
Neural Networks : the Official Journal of the International Neural Network Society|March 6, 2025
Approximation by non-symmetric networks for cross-domain learningH N Mhaskar
Neural Computation|January 1, 1997
Neural networks for functional approximation and system identificationH N Mhaskar, N Hahm
Neural Networks : the Official Journal of the International Neural Network Society|October 2, 2019
An analysis of training and generalization errors in shallow and deep networksH N Mhaskar, T Poggio
Neural Networks : the Official Journal of the International Neural Network Society|October 20, 2024
Learning on manifolds without manifold learningH N Mhaskar, Ryan O'Dowd
Journal of Computational Biology : a Journal of Computational Molecular Cell Biology|October 30, 2012
Locally learning biomedical data using diffusion framesM Ehler, F Filbir, H N Mhaskar
IEEE Transactions on Neural Networks and Learning Systems|February 10, 2021
Theory-Inspired Deep Network for Instantaneous-Frequency Extraction and Subsignals Recovery From Discrete Blind-Source DataNingning Han, H N Mhaskar, Charles K Chui
Pageof 2

Showing results (1-10 of 12) with videos related to

Sort By:
Pageof 2
Neural Networks : the Official Journal of the International Neural Network Society|August 18, 2004
When is approximation by Gaussian networks necessarily a linear process?H N Mhaskar
Neural Networks : the Official Journal of the International Neural Network Society|September 14, 2020
A direct approach for function approximation on data defined manifoldsH N Mhaskar
Neural Networks : the Official Journal of the International Neural Network Society|February 15, 2011
A generalized diffusion frame for parsimonious representation of functions on data defined manifoldsH N Mhaskar
Neural Networks : the Official Journal of the International Neural Network Society|December 24, 2019
Dimension independent bounds for general shallow networksH N Mhaskar
Neural Networks : the Official Journal of the International Neural Network Society|March 6, 2025
Approximation by non-symmetric networks for cross-domain learningH N Mhaskar
Neural Computation|January 1, 1997
Neural networks for functional approximation and system identificationH N Mhaskar, N Hahm
Neural Networks : the Official Journal of the International Neural Network Society|October 2, 2019
An analysis of training and generalization errors in shallow and deep networksH N Mhaskar, T Poggio
Neural Networks : the Official Journal of the International Neural Network Society|October 20, 2024
Learning on manifolds without manifold learningH N Mhaskar, Ryan O'Dowd
Journal of Computational Biology : a Journal of Computational Molecular Cell Biology|October 30, 2012
Locally learning biomedical data using diffusion framesM Ehler, F Filbir, H N Mhaskar
IEEE Transactions on Neural Networks and Learning Systems|February 10, 2021
Theory-Inspired Deep Network for Instantaneous-Frequency Extraction and Subsignals Recovery From Discrete Blind-Source DataNingning Han, H N Mhaskar, Charles K Chui
Pageof 2