Across the five benchmark datasets, the authors characterize ridge regression on random features as faster than and competitively accurate with alternative large-scale kernel methods, while Table 1 shows that the advantage depends on dataset and feature family rather than holding for every individual entry.

Across the five benchmark datasets, the authors characterize ridge regression on random features as faster than and competitively accurate with alternative large-scale kernel methods, while Table 1 shows that the advantage depends on dataset and feature family rather than holding for every individual entry. · CiteArk

报告指标与观测值

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