On the Absence of Spurious Local Minima in Nonlinear Low-Rank Matrix Recovery Problems

被引:0
作者
Bi, Yingjie [1 ]
Lavaei, Javad [1 ]
机构
[1] Univ Calif Berkeley, Ind Engn & Operat Res, Berkeley, CA 94720 USA
来源
24TH INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND STATISTICS (AISTATS) | 2021年 / 130卷
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D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The restricted isometry property (RIP) is a well-known condition that guarantees the absence of spurious local minima in low-rank matrix recovery problems with linear measurements. In this paper, we introduce a novel property named bound difference property (BDP) to study low-rank matrix recovery problems with nonlinear measurements. Using RIP and BDP jointly, we propose a new criterion to certify the nonexistence of spurious local minima in the rank-1 case, and prove that it leads to a much stronger theoretical guarantee than the existing bounds on RIP.
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页码:379 / +
页数:10
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