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cs.LG2022
Lower Bounds for the Convergence of Tensor Power Iteration on Random Overcomplete Models
Yuchen Wu, Kangjie Zhou
Tensor decomposition serves as a powerful primitive in statistics and machine learning, and has numerous applications in problems such as learning latent variable models or mixture…
math.ST2022
Fundamental Limits of Low-Rank Matrix Estimation with Diverging Aspect Ratios
Andrea Montanari, Yuchen Wu
We consider the problem of estimating the factors of a low-rank matrix, when this is corrupted by additive Gaussian noise. A special example of our setting corresponds…
stat.CO2022★ 2 cited
Statistically Optimal First Order Algorithms: A Proof via Orthogonalization
Andrea Montanari, Yuchen Wu
We consider a class of statistical estimation problems in which we are given a random data matrix (and possibly some labels ${\boldsymb…