arXiv Machine Learning
Aug 26

The Sharp Tail of Uniform Stability

arXiv:2608.24098v1 Announce Type: new Abstract: Uniform stability controls how much one training example can change the loss at any test point. A new logarithmic-free upper bound shows that a $\gamma...

By Pahan Dewasurendra
arXiv Machine Learning
Jun 8

Stability beyond Bounded Differences: Sharp Generalization Bounds under Finite $L_p$ Moments

arXiv:2606. 06855v1 Announce Type: cross Abstract: While algorithmic stability is a central tool for understanding generalization of learning algorithms, existing high-probability guarantees typically rely on uniform boundedness or sub-Gaussian/sub-Weibull tail assumptions, which can be overly restrictive for modern settings with heavy-tailed or unbounded losses.

By Qianqian Lei, Soham Bonnerjee, Yuefeng Han, Wei Biao Wu