Abstract: We study gradient methods for solving distributed convex optimization problems over a network when the communication bandwidth between the nodes is limited, and so information that is ...
Abstract: Owing to their solid theoretical guarantees and flexible learning framework, random features (RFs) methods have drawn increasing attention in the field of nonparametric statistical learning.
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