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Local Identifiability of $\ell_1$-minimization Dictionary Learning: a Sufficient and Almost Necessary Condition

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Figure 1: Local recovery errors for the s-sparse Gaussian model (Left) and the Bernoulli(p)-Gaussian model (Right).Under the s-sparse Gaussian model, the parameters ∈ {1,
Figure 2: Data generation for K = 2. Left: the s-sparse Gaussian model with s = 1; Right:the Bernoulli(p)-Gaussian model with p = 0.2
Figure 3: Local identifiability phase boundaries for constant inner-product dictionaries, un-der Left: the s-sparse Gaussian model; Right: the Bernoulli(p)-Gaussian model.For each model, phase boundaries for different dictionary sizes K are shown
Figure B.1: Local recovery errors for the s-sparse Gaussian model (Left) and theBernoulli(p)-Gaussian model (Right), with the number of dictionary atomsK = 20

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