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Generalization Analysis of Distributed Kernel-based Robust Gradient Descent Algorithms
In this paper, we investigate the generalization performance of distributed gradient descent algorithms in a reproducing kernel Hilbert space under a robust loss function $l_σ$. By exploiting the spectral characterization of gradient descent together with the intrinsic properties of robust loss func
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