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Orthogonal Bootstrap: Efficient Simulation of Input Uncertainty
Bootstrap is a popular methodology for simulating input uncertainty.
The Local Landscape of Phase Retrieval Under Limited Samples
We next consider the one-point strong convexity and show that as long as $n=\omega(d)$, with high probability, the landscape is one-point strongly convex in the local annulus: $\{w\in\mathbb{R}^d: o_d(1)\leqslant \|w-w^*\|\leqslant c\}$, where $w^*$ is the ground truth and $c$ is an absolute constant.
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