Department of Computer Science | Institute of Theoretical Computer Science | CADMO
Prof. Emo Welzl and Prof. Bernd Gärtner
|Mittagsseminar Talk Information|
Date and Time: Tuesday, April 03, 2012, 12:15 pm
Duration: 30 minutes
Location: CAB G51
Speaker: Sebastian Stich
The classical gradient method is one of the main pillars of the successful story of modern convex optimization. Complexity analysis has revealed that the convergence rate of the gradient method is far from the theoretical lower bound. Although optimal methods have already been proposed in the 80s, they became popular not before the last decade.
We analyze the convergence rate of the gradient method on smooth strongly convex functions and present the lower complexity bound for this class. We introduce Polyak's Heavy Ball Method. This is one of the simplest multistep schemes which does not only have an easy physical explanation, but also achieves optimal convergence rate.
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