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Optimal learning rates for distribution regression

Journal of Complexity, 2020
A learning algorithm is studied for distribution regression with regularized least squares (RLS). The algorithm contains two stages of samples and aims at regressing from distributions to real valued outputs. The first stage sample consists of (unknown) probability distributions \(x_i, i=1,\ldots,l,\) and the second stage sample consists of the data ...
Zhiying Fang   +2 more
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