High-dimensional centrally-symmetric polytopes with neighborliness proportional to dimension (2005)
| Venue: | Comput. Geometry, (online) Dec |
| Citations: | 12 - 5 self |
BibTeX
@TECHREPORT{Donoho05high-dimensionalcentrally-symmetric,
author = {David L. Donoho},
title = {High-dimensional centrally-symmetric polytopes with neighborliness proportional to dimension},
institution = {Comput. Geometry, (online) Dec},
year = {2005}
}
Years of Citing Articles
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Abstract
Let A be a d by n matrix, d < n. Let C be the regular cross polytope (octahedron) in R n. It has recently been shown that properties of the centrosymmetric polytope P = AC are of interest for finding sparse solutions to the underdetermined system of equations y = Ax; [9]. In particular, it is valuable to know that P is centrally k-neighborly. We study the face numbers of randomly-projected cross-polytopes in the proportionaldimensional case where d ∼ δn, where the projector A is chosen uniformly at random from the Grassmann manifold of d-dimensional orthoprojectors of R n. We derive ρN(δ)> 0 with the property that, for any ρ < ρN (δ), with overwhelming probability for large d, the number of k-dimensional faces of P = AC is the same as for C, for 0 ≤ k ≤ ρd. This implies that P is centrally ⌊ρd⌋-neighborly, and its skeleton Skel ⌊ρd⌋(P) is combinatorially equivalent to Skel ⌊ρd⌋(C). We display graphs of ρN. Two weaker notions of neighborliness are also important for understanding sparse solutions of linear equations: facial neighborliness and sectional neighborliness [9]; we study both. The weakest, (k, ɛ)-facial neighborliness, asks if the k-faces are all simplicial and if







