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On-line Non-Convex Constrained Optimization

16 September 2019
Olivier Massicot
Jakub Mareˇcek
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Abstract

Time-varying non-convex continuous-valued non-linear constrained optimization is a fundamental problem. We study conditions wherein a momentum-like regularising term allow for the tracking of local optima by considering an ordinary differential equation (ODE). We then derive an efficient algorithm based on a predictor-corrector method, to track the ODE solution.

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