Vasileios Sevetlidis
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126
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ML×1AI×1
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2026
A Fiber Criterion for Representation Identifiability in Supervised Learning
The paper formalizes the problem of representation identifiability in supervised learning, showing that a representation property is identifiable if and only if it is constant across all possible factorizations that yield the same overall predictor.
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