Search Results for author: Terrence WK Mak

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Lagrangian Duality for Constrained Deep Learning

no code implementations26 Jan 2020 Ferdinando Fioretto, Pascal Van Hentenryck, Terrence WK Mak, Cuong Tran, Federico Baldo, Michele Lombardi

In energy domains, the combination of Lagrangian duality and deep learning can be used to obtain state-of-the-art results to predict optimal power flows, in energy systems, and optimal compressor settings, in gas networks.

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