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stat.ML2026
The Implicit Bias of Logit Regularization
Alon Beck, Yohai Bar Sinai, Noam Levi
Logit regularization, the addition of a convex penalty directly in logit space, is widely used in modern classifiers, with label smoothing as a prominent example. While such method…
stat.ML2024
Grokking at the Edge of Linear Separability
Alon Beck, Noam Levi, Yohai Bar-Sinai
We investigate the phenomenon of grokking -- delayed generalization accompanied by non-monotonic test loss behavior -- in a simple binary logistic classification task, for which "m…
stat.ML2023
Grokking in Linear Estimators -- A Solvable Model that Groks without Understanding
Noam Levi, Alon Beck, Yohai Bar-Sinai
Grokking is the intriguing phenomenon where a model learns to generalize long after it has fit the training data. We show both analytically and numerically that grokking can surpri…