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Abstract: This article proposes a general formulation for temporal parallelization of dynamic programming for optimal control problems. We derive the elements and associative operators to be able to ...

Abstract: One often encounters the curse of dimensionality in the application of dynamic programming to determine optimal policies for controlled Markov chains. In this paper, we provide a method to ...

Our approach introduces the first general Learning-to-Optimize (L2O) framework designed for Mixed-Integer Nonlinear Programming (MINLP). As illustrated above, the approach consists of two core ...

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