S-semigoodness for Low-Rank Semidefinite Matrix Recovery

We extend and characterize the concept of s-semigoodness for a sensing matrix in sparse nonnegative recovery (proposed by Juditsky , Karzan and Nemirovski [Math Program, 2011]) to the linear transformations in low-rank semidefinite matrix recovery. We show that ssemigoodnessis not only a necessary a...

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Bibliographic Details
Main Authors: Kong, L., Sun, Jie, xiu, N.
Format: Journal Article
Published: Yokohama Publishers 2014
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/8702