Each local estimator of a decentralized robust kernel-based gradient descent achieves optimal regression rates (up to logs) when local data sizes and the robustness scale are chosen according to explicit conditions.
On regularization algorithms in learning theory, Journal of complexity, 23.1: 52-72, 2007
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Theory of Decentralized Robust Kernel-Based Learning
Each local estimator of a decentralized robust kernel-based gradient descent achieves optimal regression rates (up to logs) when local data sizes and the robustness scale are chosen according to explicit conditions.