Hrushikesh Mhaskar

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TOMASO POGGIOMcDermott Professor in Brain Sciences, MITCorreu electrònic verificat a ai.mit.edu
E. B. SaffDistinguished Professor of Mathematics, Vanderbilt UniversityCorreu electrònic verificat a vanderbilt.edu
Jürgen PrestinProfessor für Mathematik, Universität zu LübeckCorreu electrònic verificat a math.uni-luebeck.de
J. D. WardProfessor emeritus of mathematics, Texas A&M UniversityCorreu electrònic verificat a math.tamu.edu
Lorenzo RosascoMaLGa Machine Learning Genoa Center - Università degli Studi di GenovaCorreu electrònic verificat a unige.it
Brando MirandaMIT, UIUC, StanfordCorreu electrònic verificat a stanford.edu
D.S. LubinskyCorreu electrònic verificat a math.gatech.edu
Sergei PereverzevProfessor, Johann Radon Institute for Computational and Applied Mathematics, Austrian Academy ofCorreu electrònic verificat a oeaw.ac.at
Maria D. van der WaltWestmont CollegeCorreu electrònic verificat a westmont.edu
Karthik Jayaraman RaghuramApple IncCorreu electrònic verificat a apple.com
Alexander CloningerAssociate Professor, Department of Mathematics & Halicioglu Data Science Institute, UC San DiegoCorreu electrònic verificat a ucsd.edu
Mauro MaggioniBloomberg Distinguished Professor of Mathematics, and Applied Mathematics and StatisticsCorreu electrònic verificat a jhu.edu
Mahadevan GaneshColorado School of MinesCorreu electrònic verificat a mines.edu
Ian SloanProfessor of Mathematics, University of New South Wales (UNSW Australia)Correu electrònic verificat a unsw.edu.au
Azita MayeliProfessor of Mathematics at the City University of New YorkCorreu electrònic verificat a gc.cuny.edu
ISAAC PESENSONProfessor of Mathematics, Temple UniversityCorreu electrònic verificat a temple.edu
Xiaosheng ZhuangCity University of Hong KongCorreu electrònic verificat a cityu.edu.hk
Valeriya NaumovaSimula Research LaboratoryCorreu electrònic verificat a simula.no
Dmitry BatenkovBasis Research InstituteCorreu electrònic verificat a basis.ai
Narendra GOVILDepartment of Mathematics and Statistics, Auburn UniversityCorreu electrònic verificat a auburn.edu

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Hrushikesh Mhaskar

Distinguished Research Professor, Claremont Graduate University

Correu electrònic verificat a cgu.edu

Applied and computational harmonic analysis approximation theory learning theory data/image


Títol Ordena per cites Ordena per any Ordena per títol	Citada per Citada per	Any
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	771	2017
Neural networks for optimal approximation of smooth and analytic functions HN Mhaskar Neural computation 8 (1), 164-177, 1996	482	1996
Deep vs. shallow networks: An approximation theory perspective HN Mhaskar, T Poggio Analysis and Applications 14 (06), 829-848, 2016	459	2016
Approximation by superposition of sigmoidal and radial basis functions HN Mhaskar, CA Micchelli Advances in Applied mathematics 13 (3), 350-373, 1992	385	1992
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	286	1985
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	268	2017
Spherical Marcinkiewicz-Zygmund inequalities and positive quadrature H Mhaskar, F Narcowich, J Ward Mathematics of computation 70 (235), 1113-1130, 2001	256	2001
Extremal problems for polynomials with exponential weights HN Mhaskar, EB Saff Transactions of the American Mathematical Society 285 (1), 203-234, 1984	243	1984
Introduction to the theory of weighted polynomial approximation HN Mhaskar World Scientific, 1996	224	1996
Approximation properties of a multilayered feedforward artificial neural network HN Mhaskar Advances in Computational Mathematics 1 (1), 61-80, 1993	220	1993
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	191	1995
Learning functions: when is deep better than shallow H Mhaskar, Q Liao, T Poggio arXiv preprint arXiv:1603.00988, 2016	183	2016
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	158	2017
Fundamentals of approximation theory HN Mhaskar, DV Pai CRC Press, 2000	144	2000
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	138	2017
Neural networks for localized approximation CK Chui, X Li, HN Mhaskar mathematics of computation 63 (208), 607-623, 1994	130	1994
A proof of Freud's conjecture for exponential weights DS Lubinsky, HN Mhaskar, EB Saff Constructive Approximation 4, 65-83, 1988	126	1988
On trigonometric wavelets CK Chui, HN Mhaskar Constructive Approximation 9, 167-190, 1993	120	1993
Diffusion polynomial frames on metric measure spaces M Maggioni, HN Mhaskar Applied and Computational Harmonic Analysis 24 (3), 329-353, 2008	110	2008
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	102	1994

En aquests moments el sistema no pot dur a terme l'operació. Torneu-ho a provar més tard.

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