A canonical structure via linear transformation enables projected first-order algorithms with delayed feedback to reach the optimum at the same rate as their unconstrained versions.
Non-ergodic linear convergence property of the delayed gradient descent under the strongly convexity and the polyak–łojasiewicz condition
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A Canonical Structure for Constructing Projected First-Order Algorithms With Delayed Feedback
A canonical structure via linear transformation enables projected first-order algorithms with delayed feedback to reach the optimum at the same rate as their unconstrained versions.