An elementary approach to tight worst case complexity analysis of gradient based methods

This work presents a novel analysis that allows to achieve tight complexity bounds of gradient-based methods for convex optimization. We start by identifying some of the pitfalls rooted in the classical complexity analysis of the gradient descent method, and show how they can be remedied. Our method...

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