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The price of ignorance: how much does it cost to forget noise structure in low-rank matrix estimation?
We consider the problem of estimating a rank-1 signal corrupted by structured rotationally invariant noise, and address the following question: how well do inference algorithms perform when the noise statistics is unknown and hence Gaussian noise is assumed?
Performance of Bayesian linear regression in a model with mismatch
Here we consider a model in which the responses are corrupted by gaussian noise and are known to be generated as linear combinations of the covariates, but the distributions of the ground-truth regression coefficients and of the noise are unknown.
Strong replica symmetry for high-dimensional disordered log-concave Gibbs measures
We consider a generic class of log-concave, possibly random, (Gibbs) measures.
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