Generalization is a testable hedging property of the learner's response law, recovered via f-divergence regularizers that induce information-geometric curves between training loss and sample dependence.
Deep Double Descent: Where Bigger Models and More Data Hurt.Journal of Statistical Mechanics: Theory and Experiment, 2021(12):124003, 2021
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Bounded-Rationality, Hedging, and Generalization
Generalization is a testable hedging property of the learner's response law, recovered via f-divergence regularizers that induce information-geometric curves between training loss and sample dependence.