Hardness of Low Rank Approximation of Entrywise Transformed Matrix Products
–Neural Information Processing Systems
Some related lower bounds include the work of Backurs et al. [2017] that solving kernel Support V ector Machines (SVM), ridge regression, or Principal Component Analysis (PCA) problems to high accuracy or approximating kernel density estimates up to a constant factor for kernels with
Neural Information Processing Systems
Oct-9-2025, 03:42:24 GMT
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