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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