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Learning learning-augmented algorithms. The example of stochastic scheduling

Vianney Perchet (ENSAE Paris)
E18-304

Abstract: In this talk, I will argue that it is sometimes possible to learn, with techniques originated from bandits, the "hints" on which learning-augmented algorithms rely to improve worst-case performances. We will describe this phenomenon, the combination of online learning with competitive analysis, on the example of stochastic online scheduling. We shall quantify the merits of this approach by computing and comparing non-asymptotic expected competitive ratios (the standard performance measure of algorithms) Bio: Vianney Perchet is a professor at the…

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