Hrushikesh Mhaskar
Titel
Zitiert von
Zitiert von
Jahr
Approximation by superposition of sigmoidal and radial basis functions
HN Mhaskar, CA Micchelli
Advances in Applied mathematics 13 (3), 350-373, 1992
3121992
Neural networks for optimal approximation of smooth and analytic functions
HN Mhaskar
Neural computation 8 (1), 164-177, 1996
2771996
Where does the sup norm of a weighted polynomial live?
HN Mhaskar, EB Saff
Constructive Approximation 1 (1), 71-91, 1985
2671985
Extremal problems for polynomials with exponential weights
HN Mhaskar, EB Saff
Transactions of the American Mathematical Society 285 (1), 203-234, 1984
2301984
Spherical Marcinkiewicz-Zygmund inequalities and positive quadrature
H Mhaskar, F Narcowich, J Ward
Mathematics of computation 70 (235), 1113-1130, 2001
2002001
Introduction to the theory of weighted polynomial approximation
HN Mhaskar
World Scientific, 1997
1981997
Why and when can deep-but not shallow-networks avoid the curse of dimensionality: a review
T Poggio, H Mhaskar, L Rosasco, B Miranda, Q Liao
International Journal of Automation and Computing 14 (5), 503-519, 2017
1952017
Deep vs. shallow networks: An approximation theory perspective
HN Mhaskar, T Poggio
Analysis and Applications 14 (06), 829-848, 2016
1782016
Degree of approximation by neural and translation networks with a single hidden layer
CA Micchelli
Advances in applied mathematics 16, 151-183, 1995
1451995
Approximation properties of a multilayered feedforward artificial neural network
HN Mhaskar
Advances in Computational Mathematics 1 (1), 61-80, 1993
1311993
On trigonometric wavelets
CK Chui, HN Mhaskar
Constructive Approximation 9 (2-3), 167-190, 1993
1091993
Fundamentals of approximation theory
HN Mhaskar, DV Pai
CRC Press, 2000
1042000
A proof of Freud's conjecture for exponential weights
DS Lubinsky, HN Mhaskar, EB Saff
Constructive Approximation 4 (1), 65-83, 1988
1011988
Neural networks for localized approximation
CK Chui, X Li, HN Mhaskar
Mathematics of Computation 63 (208), 607-623, 1994
841994
Dimension-independent bounds on the degree of approximation by neural networks
HN Mhaskar, CA Micchelli
IBM Journal of Research and Development 38 (3), 277-284, 1994
831994
Learning functions: when is deep better than shallow
H Mhaskar, Q Liao, T Poggio
arXiv preprint arXiv:1603.00988, 2016
822016
Diffusion polynomial frames on metric measure spaces
M Maggioni, HN Mhaskar
Applied and Computational Harmonic Analysis 24 (3), 329-353, 2008
802008
When and why are deep networks better than shallow ones?
H Mhaskar, Q Liao, T Poggio
Thirty-First AAAI Conference on Artificial Intelligence, 2017
762017
Approximation properties of zonal function networks using scattered data on the sphere
HN Mhaskar, FJ Narcowich, JD Ward
Advances in Computational Mathematics 11 (2-3), 121-137, 1999
751999
Where does the 𝐿^{𝑝}-norm of a weighted polynomial live?
HN Mhaskar, EB Saff
Transactions of the American Mathematical Society 303 (1), 109-124, 1987
671987
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