Electrical Engineering and Systems Science > Systems and Control
[Submitted on 29 Jan 2023 (v1), last revised 6 Apr 2023 (this version, v2)]
Title:Stochastic Wasserstein Gradient Flows using Streaming Data with an Application in Predictive Maintenance
View PDFAbstract:We study estimation problems in safety-critical applications with streaming data. Since estimation problems can be posed as optimization problems in the probability space, we devise a stochastic projected Wasserstein gradient flow that keeps track of the belief of the estimated quantity and can consume samples from online data. We show the convergence properties of our algorithm. Our analysis combines recent advances in the Wasserstein space and its differential structure with more classical stochastic gradient descent. We apply our methodology for predictive maintenance of safety-critical processes: Our approach is shown to lead to superior performance when compared to classical least squares, enabling, among others, improved robustness for decision-making.
Submission history
From: Nicolas Lanzetti [view email][v1] Sun, 29 Jan 2023 15:18:48 UTC (5,317 KB)
[v2] Thu, 6 Apr 2023 16:51:13 UTC (5,319 KB)
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