Feature-distributed sparse regression: a screen-and-clean approach


Most existing approaches to distributed sparse regression assume the data is partitioned by samples. However, for high-dimensional data (D N ), it is more natural to partition the data by features. We propose an algorithm to distributed sparse regression when the data is partitioned by features rather than samples. Our approach allows the user to tailor our… (More)

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