Wednesday, July 12

MS46
Nonlinear Approximation

4:00 PM-6:00 PM
Rio Mar 3

Nonlinear approximation seeks ways to approximate complicated functions by simple functions using methods that depend nonlinearly on the function being approximated. Such methods of approximation are more flexible than traditional linear approximation methods and proved to be very useful in various applications such as image compression, signal processing, design of neural networks, and the numerical solution of nonlinear partial differential equations. The purpose of the proposed minisymposium is to discuss recent investigations of nonlinear approximation. Emphasis will be placed on studying the efficiency of algorithms which are important in practical applications. Intended audience: Imaging, Nonlinear PDE, Optimization.

4:00-4:25 Greedy Algorithms in Nonlinear Approximation

Vladimir Temlyakov, Organizer

4:30-4:55 Nonlinear Approximation - Some Applications in Numerical Analysis

Wolfgang Dahmen, Institut für Geometrie und Praktische Mathematik, Germany; Albert Cohen, Université Pierre e Marie Curie, France; and Ronald A. DeVore, University of South Carolina, USA

5:00-5:25 One-Bit Quantization of Bandlimited Functions

C. Sinan Güntürk, Princeton University, USA

5:30-5:55 Some Recent Developments in Ridge Approximation

Konstantin I. Oskolkov, University of South Carolina, USA

6:00-6:25 Curvelets, Anisotropy Scaling and Efficient Representations of Objects with Singularities Along Curves

E. J. Candès and David L. Donoho, Stanford University, USA