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David Donoho auf dem Internationalen Mathematikerkongress 2018. David Leigh Donoho (* 5.März 1957 in Los Angeles) ist ein US-amerikanischer Statistiker.. Donoho studierte Statistik an der Princeton University (Bachelor-Abschluss summa cum laude bei John W. Tukey) und promovierte 1983 bei Peter Huber an der Harvard University (A tool for research in data analysis), während er gleichzeitig ...
David Leigh Donoho (born March 5, 1957) is an American statistician. He is a professor of statistics at Stanford University, where he is also the Anne T. and Robert M. Bass Professor in the Humanities and Sciences. [1] His work includes the development of effective methods for the construction of low-dimensional representations for high ...
2535. 2009. Hessian eigenmaps: Locally linear embedding techniques for high-dimensional data. DL Donoho, C Grimes. Proceedings of the National Academy of Sciences 100 (10), 5591-5596. , 2003. 2266. 2003. New tight frames of curvelets and optimal representations of objects with piecewise C2 singularities.
David Donoho has studied the exploitation of sparse signals in signal recovery, including for denoising, superresolution, and solution of underdetermined equations. His research with collaborators showed that ell-1 penalization was an effective and even optimal way to exploit sparsity of the object to be recovered.
Foreign Associate, Académie des Sciences (France), 2010. Von Neumann Prize Lecturer, Soc. Indus. Appl. Math. 2001. Election to National Academy of Sciences, USA, 1998. Presidents’ Award, Committee of Presidents of Statistical Societies, 1994. Election to American Academy of Arts and Sciences, 1992.
home - dave donoho. My theoretical research interests have focused on the mathematics of statistical inference and on theoretical questions arising in applying harmonic analysis to various applied problems. My applied research interests have ranged from data visualization to various problems in scientific signal processing, image processing ...
Professor David Donoho is the Anne T. and Robert M. Bass Professor of Humanities and Sciences and Professor of Statistics at Stanford University. He has made fundamental contributions to theoretical and computational statistics, and his algorithms have contributed significantly to our understanding of how to work with sparse data.
