Abstract
Algorithms for sparse recovery problems from non-linear measurements have attracted some attention lately. Closely related to the problem of sparse is recovery is the problem of low-rank matrix recovery. There is no work on the topic of low-rank matrix recovery from non-linear measurements. This is the first study that proposes two algorithms for the said problem. The first one is based on nuclear norm minimization while the second one is based on Ky-Fan norm minimization.
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