### Martin Lotz (University of Oxford)

#### Probabilistic analysis of condition numbers in linear and conic programming

*Joint work with Peter Buergisser and Felipe Cucker.*

*Wednesday 18 November 2009 at 15.30, JCMB 6206*

##### Abstract

The complexity of iterative algorithms in numerical analysis often depends on
the condition number of the input (for example, conjugate gradient method).
Similarly, condition numbers have been introduced in the context of linear
and conic programming, and play a role in the complexity analysis of interior
point methods (among other things). In this talk I will discuss geometric
measures of condition for linear and conic programming and present results
about the probability distribution of these condition numbers on random
inputs. As a consequence we obtain average-case complexity results for
algorithms solving the conic feasibility problem.

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