Finding Structure and Causality in Linear ProgramsDownload PDF

Published: 25 Mar 2022, Last Modified: 12 Mar 2024ICLR2022 OSC PosterReaders: Everyone
Keywords: linear programs, structure, causality, graph learning
Abstract: Linear Programs (LP) are celebrated widely, particularly so in machine learning where they have allowed for effectively solving probabilistic inference tasks or imposing structure on end-to-end learning systems. Their potential might seem depleted but we propose a foundational, causal perspective that reveals intriguing intra- and inter-structure relations for LP components. We conduct a systematic, empirical investigation on general-, shortest path- and energy system LPs.
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