SOURCE-LINKED INTELLIGENCE
Skeletal Prototypes on Iterative Nerve Expansions
Prototype reduction replaces a training set with a smaller representation, and the established methods return a finite set of points. We propose Skeletal Prototypes on Iterative Nerve Expansions (SPINE). The model for each class is an embedded 1-complex rather than a point set. Its initial edge set is a class-conditional Mapper graph, so the data decide which localized clusters are joined. Later phases fit the vertices under a classification objective, and an observation is assigned to the class whose complex is nearest. The segments therefore enter the decision rule and not only the fitting.
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-14T18:07:45.000Z
First collected: 2026-09-20T09:41:04.278Z. This is not the publication date.