Optimal Tuning for Divide-and-conquer Kernel Ridge Regression with Massive Data

Divide-and-conquer is a powerful approach for large and massive data analysis. In the nonparameteric regression setting, although various theoretical frameworks have been established to achieve optimality in estimation or hypothesis testing, how to choose the tuning parameter in a practically effective way is still an open problem... (read more)

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