On the geometric mechanics of assignment flows for metric data labeling

Metric data labeling refers to the task of assigning one of multiple predefined labels to every given datapoint based on the metric distance between label and data. This assignment of labels typically takes place in a spatial or spatio-temporal context. Assignment flows are a class of dynamical mode...

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Bibliographic Details
Main Authors: Savarino, Fabrizio (Author) , Albers, Peter (Author) , Schnörr, Christoph (Author)
Format: Article (Journal) Chapter/Article
Language:English
Published: 3 Nov 2021
In: Arxiv
Year: 2021, Pages: 1-22
DOI:10.48550/arXiv.2111.02543
Online Access:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.48550/arXiv.2111.02543
Verlag, lizenzpflichtig, Volltext: http://arxiv.org/abs/2111.02543
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Author Notes:Fabrizio Savarino, Peter Albers, Christoph Schnörr
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Summary:Metric data labeling refers to the task of assigning one of multiple predefined labels to every given datapoint based on the metric distance between label and data. This assignment of labels typically takes place in a spatial or spatio-temporal context. Assignment flows are a class of dynamical models for metric data labeling that evolve on a basic statistical manifold, the so called assignment manifold, governed by a system of coupled replicator equations. In this paper we generalize the result of a recent paper for uncoupled replicator equations and adopting the viewpoint of geometric mechanics, relate assignment flows to critical points of an action functional via the associated Euler-Lagrange equation. We also show that not every assignment flow is a critical point and characterize precisely the class of coupled replicator equations fulfilling this relation, a condition that has been missing in recent related work. Finally, some consequences of this connection to Lagrangian mechanics are investigated including the fact that assignment flows are, up to initial conditions of measure zero, reparametrized geodesics of the so-called Jacobi metric.
Item Description:Gesehen am 12.07.2022
Physical Description:Online Resource
DOI:10.48550/arXiv.2111.02543