Hrushikesh Mhaskar 个人学术档案

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TOMASO POGGIOMcDermott Professor in Brain Sciences, MIT在 ai.mit.edu 的电子邮件经过验证
E. B. SaffProfessor of Mathematics, Vanderbilt University在 vanderbilt.edu 的电子邮件经过验证
Jürgen PrestinProfessor für Mathematik, Universität zu Lübeck在 math.uni-luebeck.de 的电子邮件经过验证
J. D. WardProfessor emeritus of mathematics, Texas A&M University在 math.tamu.edu 的电子邮件经过验证
Lorenzo RosascoMaLGa Machine Learning Genoa Center - Università degli Studi di Genova在 unige.it 的电子邮件经过验证
Brando MirandaMIT, UIUC, Stanford在 stanford.edu 的电子邮件经过验证
D.S. Lubinsky在 math.gatech.edu 的电子邮件经过验证
Sergei PereverzevProfessor, Johann Radon Institute for Computational and Applied Mathematics, Austrian Academy of在 oeaw.ac.at 的电子邮件经过验证
Maria D. van der WaltWestmont College在 westmont.edu 的电子邮件经过验证
Mauro MaggioniBloomberg Distinguished Professor of Mathematics, and Applied Mathematics and Statistics在 jhu.edu 的电子邮件经过验证
Alexander CloningerAssociate Professor, Department of Mathematics & Halicioglu Data Science Institute, UC San Diego在 ucsd.edu 的电子邮件经过验证
Mahadevan GaneshColorado School of Mines在 mines.edu 的电子邮件经过验证
Ian SloanProfessor of Mathematics, University of New South Wales (UNSW Australia)在 unsw.edu.au 的电子邮件经过验证
Azita MayeliProfessor of Mathematics at the City University of New York在 gc.cuny.edu 的电子邮件经过验证
ISAAC PESENSONProfessor of Mathematics, Temple University在 temple.edu 的电子邮件经过验证
Xiaosheng ZhuangCity University of Hong Kong在 cityu.edu.hk 的电子邮件经过验证
Valeriya NaumovaSimula Research Laboratory在 simula.no 的电子邮件经过验证
Dmitry BatenkovAssistant Professor of Applied Mathematics, Tel-Aviv University, Israel在 tauex.tau.ac.il 的电子邮件经过验证
Narendra GOVILDepartment of Mathematics and Statistics, Auburn University在 auburn.edu 的电子邮件经过验证
Sergey TikhonovICREA Research Professor at CRM在 crm.cat 的电子邮件经过验证

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Hrushikesh Mhaskar

Claremont Graduate University

在 cgu.edu 的电子邮件经过验证

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


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
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	685	2017
Neural networks for optimal approximation of smooth and analytic functions HN Mhaskar Neural computation 8 (1), 164-177, 1996	462	1996
Deep vs. shallow networks: An approximation theory perspective HN Mhaskar, T Poggio Analysis and Applications 14 (06), 829-848, 2016	428	2016
Approximation by superposition of sigmoidal and radial basis functions HN Mhaskar, CA Micchelli Advances in Applied mathematics 13 (3), 350-373, 1992	371	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	281	1985
Spherical Marcinkiewicz-Zygmund inequalities and positive quadrature H Mhaskar, F Narcowich, J Ward Mathematics of computation 70 (235), 1113-1130, 2001	250	2001
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	242	2017
Extremal problems for polynomials with exponential weights HN Mhaskar, EB Saff Transactions of the American Mathematical Society 285 (1), 203-234, 1984	242	1984
Introduction to the theory of weighted polynomial approximation HN Mhaskar World Scientific, 1996	217	1996
Approximation properties of a multilayered feedforward artificial neural network HN Mhaskar Advances in Computational Mathematics 1 (1), 61-80, 1993	212	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	180	1995
Learning functions: when is deep better than shallow H Mhaskar, Q Liao, T Poggio arXiv preprint arXiv:1603.00988, 2016	176	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	141	2017
Fundamentals of approximation theory HN Mhaskar, DV Pai CRC Press, 2000	133	2000
Neural networks for localized approximation CK Chui, X Li, HN Mhaskar mathematics of computation 63 (208), 607-623, 1994	128	1994
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	127	2017
A proof of Freud's conjecture for exponential weights DS Lubinsky, HN Mhaskar, EB Saff Constructive Approximation 4, 65-83, 1988	125	1988
On trigonometric wavelets CK Chui, HN Mhaskar Constructive Approximation 9, 167-190, 1993	119	1993
Diffusion polynomial frames on metric measure spaces M Maggioni, HN Mhaskar Applied and Computational Harmonic Analysis 24 (3), 329-353, 2008	107	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	99	1994

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