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Regularization: Quadratic Versus Sparsity-enforcing and Deterministic Versus Stochastic Methods

Regularization: Quadratic Versus Sparsity-enforcing and Deterministic Versus Stochastic Methods

This video was recorded at Workshop on Inverse Problems: Econometry, Numerical Analysis and Optimization, Statistics, Touluse 2005. What statisticians, numericians, engineers or econometricians mean by "inverse problem" often differs. For a statistician, an inverse problem is an estimation problem of a function which is not directly observed. The data are finite in number and contain errors, whose variance decreases with the number of observations, as they do in classical inference problems, while the unknown typically is infinite dimensional, as it is in nonparametric regression. For numericians, the noise is more an error induced by the fact that the real data are not directly observed. But the asymptotics differ, as the regularity conditions imposed for the solution. Finally, in... Show More
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