This study delves into the intricacies of non-convex optimization in matrix sensing problems. The introduction of high-order loss functions is shown to enhance convergence and facilitate escape from spurious local minima. Theoretical insights are supported by empirical experiments showcasing accelerated convergence and favorable geometric properties far from the ground truth.
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by Ziye Ma,Ying... at arxiv.org 03-12-2024
https://arxiv.org/pdf/2403.06056.pdfDeeper Inquiries