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Optimal Pruning for Neural Architectures using Fisher Information Distances

This story is from 2026-09-16. It is preserved in the archive; the latest stories are on the live feed.

arXiv:2609.16129v1 Announce Type: new Abstract: A new scheme for parameter pruning is introduced, derived from the differential-geometric distance in model space. Pruning a parameter sets its value to zero, representing a displacement of the model to the hypersurface on which that parameter vanishe…

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  1. 2026-09-16 04:00 · arXiv cs.AI
    Optimal Pruning for Neural Architectures using Fisher Information Distances

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