Sample-Based Neural Approximation Approach for Probabilistic Constrained Programs.
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DOI: 10.1109/tnnls.2021.3102323
Abstract: This article introduces a neural approximation-based method for solving continuous optimization problems with probabilistic constraints. After reformulating the probabilistic constraints as the quantile function, a sample-based neural network model is used to approximate the quantile… read more here.
Keywords: based neural; sample based; neural approximation; probabilistic constrained ... See more keywords