An Online-Learning Approach to Inverse Optimization

30 Oct 2018Andreas BärmannAlexander MartinSebastian PokuttaOskar Schneider

In this paper, we demonstrate how to learn the objective function of a decision-maker while only observing the problem input data and the decision-maker's corresponding decisions over multiple rounds. We present exact algorithms for this online version of inverse optimization which converge at a rate of $ \mathcal{O}(1/\sqrt{T}) $ in the number of observations~$T$ and compare their further properties... (read more)

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