Nearly minimax-optimal rates for noisy sparse phase retrieval via early-stopped mirror descent
This paper studies early-stopped mirror descent applied to noisy sparse phase retrieval, which is the problem of recovering a k-sparse signal x ? ∈ R n from a set of quadratic Gaussian measurements corrupted by sub-exponential noise. We consider the (non-convex) unregularized empirical risk minimiza...
| Main Authors: | , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Oxford University Press
2022
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