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.
Learning theory: An Approximation Theory Viewpoint
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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.