The low-degree likelihood ratio method predicts computational hardness of hypothesis testing problems, with new connections to spectral methods and a lower bound for tensor PCA.
Algorithmic thresholds for tensor PCA
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Notes on Computational Hardness of Hypothesis Testing: Predictions using the Low-Degree Likelihood Ratio
The low-degree likelihood ratio method predicts computational hardness of hypothesis testing problems, with new connections to spectral methods and a lower bound for tensor PCA.