Stephen Smale
Affiliations: | TTI Chicago, Chicago, IL, United States | ||
Mathematics | University of California, Berkeley, Berkeley, CA, United States |
Area:
Algorithms, Numerical analysis, Global analysisWebsite:
http://ttic.uchicago.edu/~smale/vita.htmlGoogle:
"Stephen Smale"Bio:
http://www-gap.dcs.st-and.ac.uk/~history/Mathematicians/Smale.html
http://www.genealogy.math.ndsu.nodak.edu/id.php?id=5086
Born in Michigan, USA, Professor Smale received his PhD degree from the University of Michigan in 1957, and within four years became a full Professor at Columbia University. In 1964, he was named a Professor at the University of California, Berkeley and held the post for 30 years before joining City University as a Distinguished University Professor.
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Mean distance: 18.43
Cross-listing: MathTree - Econometree
Parents
Sign in to add mentorRaoul Bott | grad student | 1957 | University of Michigan (MathTree) | |
(Regular Curves on Riemannian Manifolds.) |
Children
Sign in to add traineeNancy Kopell | grad student | ||
Morris W. Hirsch | grad student | 1958 | Chicago (MathTree) |
John Guckenheimer | grad student | 1970 | UC Berkeley (Physics Tree) |
Julian Palmore | grad student | 1973 | UC Berkeley (MathTree) |
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Publications
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Hirsch MW, Smale S, Devaney RL. (2013) Differential Equations, Dynamical Systems, and an Introduction to Chaos Differential Equations, Dynamical Systems, and An Introduction to Chaos |
Bartholdi L, Schick T, Smale N, et al. (2012) Hodge Theory on Metric Spaces Foundations of Computational Mathematics. 12: 1-48 |
Smale S, Rosasco L, Bouvrie J, et al. (2010) Mathematics of the neural response Foundations of Computational Mathematics. 10: 67-91 |
Smale S, Zhou D. (2009) Online Learning With Markov Sampling Analysis and Applications. 7: 87-113 |
Smale S, Zhou DX. (2009) Geometry on probability spaces Constructive Approximation. 30: 311-323 |
Smale S, Yao Y. (2006) Online learning algorithms Foundations of Computational Mathematics. 6: 145-170 |
Smale S, Zhou DX. (2005) Shannon sampling II: Connections to learning theory Applied and Computational Harmonic Analysis. 19: 285-302 |
Poggio T, Smale S. (2005) The mathematics of learning: Dealing with data Proceedings of 2005 International Conference On Neural Networks and Brain Proceedings, Icnnb'05. 1: PL-5-PL-23 |
Cucker F, Smale S. (2002) Best Choices for Regularization Parameters in Learning Theory: On the Bias-Variance Problem Foundations of Computational Mathematics. 2: 413-428 |
Blum L, Cucker F, Shub M, et al. (1996) Complexity and real computation: A manifesto International Journal of Bifurcation and Chaos in Applied Sciences and Engineering. 6: 3-26 |