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Dr. Dennis Amelunxen
KontaktCity University of Hong Kong
Department of Mathematics
G6613 (Green Zone), 6/F Academic 1
Tat Chee Avenue, Kowloon Tong, Hong Kong Persönliche Homepage
sites.google.com/site/dennisamelunxen/home
Publikationen in der Arbeitsgruppe
Citation key | AB-Probabilistic-Analysis-Of-The-Grassmann-Condition-Number |
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Author | Dennis Amelunxen and Peter Bürgisser |
Pages | 3-51 |
Year | 2015 |
Journal | Foundations of Computational Mathematics |
Volume | 15 |
Number | 1 |
Month | 02 |
Abstract | We analyze the probability that a random $m$-dimensional linear subspace of $IR^n$ both intersects a regular closed convex cone $C\subseteq IR^n$ and lies within distance α of an $m$-dimensional subspace not intersecting $C$ (except at the origin). The result is expressed in terms of the spherical intrinsic volumes of the cone $C$. This allows us to perform an average analysis of the Grassmann condition number $CG(A)$ for the homogeneous convex feasibility problem $\exists x\in C\setminus0:Ax=0$. The Grassmann condition number is a geometric version of Renegar's condition number, that we have introduced recently in [SIOPT 22(3):1029–1041, 2012]. We thus give the first average analysis of convex programming that is not restricted to linear programming. In particular, we prove that if the entries of $A\in IR^m× n$ are chosen i.i.d. standard normal, then for any regular cone $C$, we have $ IE[łn CG(A)]<1.5łn(n)+1.5$. The proofs rely on various techniques from Riemannian geometry applied to Grassmann manifolds. |