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Hrushikesh Mhaskar
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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
7402017
Neural networks for optimal approximation of smooth and analytic functions
HN Mhaskar
Neural computation 8 (1), 164-177, 1996
4711996
Deep vs. shallow networks: An approximation theory perspective
HN Mhaskar, T Poggio
Analysis and Applications 14 (06), 829-848, 2016
4492016
Approximation by superposition of sigmoidal and radial basis functions
HN Mhaskar, CA Micchelli
Advances in Applied mathematics 13 (3), 350-373, 1992
3811992
Where does the sup norm of a weighted polynomial live? A Generalization of Incomplete Polynomials
HN Mhaskar, EB Saff
Constructive Approximation 1, 71-91, 1985
2851985
When and why are deep networks better than shallow ones?
H Mhaskar, Q Liao, T Poggio
Proceedings of the AAAI conference on artificial intelligence 31 (1), 2017
2622017
Spherical Marcinkiewicz-Zygmund inequalities and positive quadrature
H Mhaskar, F Narcowich, J Ward
Mathematics of computation 70 (235), 1113-1130, 2001
2552001
Extremal problems for polynomials with exponential weights
HN Mhaskar, EB Saff
Transactions of the American Mathematical Society 285 (1), 203-234, 1984
2431984
Introduction to the theory of weighted polynomial approximation
HN Mhaskar
World Scientific, 1996
2221996
Approximation properties of a multilayered feedforward artificial neural network
HN Mhaskar
Advances in Computational Mathematics 1 (1), 61-80, 1993
2191993
Degree of approximation by neural and translation networks with a single hidden layer
HN Mhaskar, CA Micchelli
Advances in applied mathematics 16 (2), 151-183, 1995
1871995
Learning functions: when is deep better than shallow
H Mhaskar, Q Liao, T Poggio
arXiv preprint arXiv:1603.00988, 2016
1812016
A deep learning approach to diabetic blood glucose prediction
HN Mhaskar, SV Pereverzyev, MD Van der Walt
Frontiers in applied mathematics and statistics 3, 14, 2017
1512017
Fundamentals of approximation theory
HN Mhaskar, DV Pai
CRC Press, 2000
1412000
Theory of deep learning III: explaining the non-overfitting puzzle
T Poggio, K Kawaguchi, Q Liao, B Miranda, L Rosasco, X Boix, J Hidary, ...
arXiv preprint arXiv:1801.00173, 2017
1362017
Neural networks for localized approximation
CK Chui, X Li, HN Mhaskar
mathematics of computation 63 (208), 607-623, 1994
1291994
A proof of Freud's conjecture for exponential weights
DS Lubinsky, HN Mhaskar, EB Saff
Constructive Approximation 4, 65-83, 1988
1241988
On trigonometric wavelets
CK Chui, HN Mhaskar
Constructive Approximation 9, 167-190, 1993
1201993
Diffusion polynomial frames on metric measure spaces
M Maggioni, HN Mhaskar
Applied and Computational Harmonic Analysis 24 (3), 329-353, 2008
1102008
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
1021994
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