Abstract
In this paper, we study the Riemannian length of the primal central path in a convex set computed with respect to the local metric defined by a self-concordant function. Despite some negative examples, in many important situations, the length of this path is quite close to the length of a geodesic curve. We show that in the case of a bounded convex set endowed with a ν-self-concordant barrier, the length of the central path is within a factor O(ν 1/4) of the length of the shortest geodesic curve.
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Communicated by Mike Todd.
This paper presents research results of the Belgian Program on Interuniversity Poles of Attraction initiated by the Belgian State, Prime Minister’s Office, Science Policy Programming.
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Nesterov, Y., Nemirovski, A. Primal Central Paths and Riemannian Distances for Convex Sets. Found Comput Math 8, 533–560 (2008). https://doi.org/10.1007/s10208-007-9019-4
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DOI: https://doi.org/10.1007/s10208-007-9019-4
Keywords
- Riemannian geometry
- Convex optimization
- Structural optimization
- Interior-point methods
- Path-following methods
- Self-concordant functions
- Polynomial-time methods