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On the Nonoccurrence of Gradient Restart in Nesterov Accelerated Gradient Method
Gradient restarting often improves the practical performance of accelerated gradient methods for unconstrained convex optimization problems, but a general theoretical guarantee of such improvement remains unclear. In this paper, we construct smooth, strongly convex objectives with Lipschitz-continuo
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