### Iterative Algorithms

Montanari, A *(Stanford)*

Tuesday 12 January 2010, 09:30-10:30

Seminar Room 1, Newton Institute

#### Abstract

The problem of estimating a high dimensional vector from a set of linear
observations arises in a number of engineering disciplines. It becomes
particularly challenging when the underlying signal has some non-linear
structure that needs to be exploited.
I will present a new class of iterative algorithms inspired by probabilistic
graphical models ideas, that appear to be asymptotically optimal in specific
contexts. I will discuss in particular the application to compressed sensing
problems.
[Joint work with David L. Donoho and Arian Maleki]

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