stat.ML · 2026-08-11 · No. 81

Machine Learning, 2026-08-11.

2 new papers in stat.ML. Titles, authors, abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →

01 — The papers

2 entries
  1. 01

    Logarithmic-Free Moment and Generalization Bounds for Uniformly Stable Algorithms

    Thanh Nguyen-Cung, Binh T. Nguyen

    stat.ML · cs.LG · math.PR · math.ST

    Uniform stability is a classical tool for controlling the generalization error of a learning algorithm. Bousquet, Klochkov, and Zhivotovskiy (2020) showed that the problem can be reduced to a moment inequality for a sum of weakly interacting functions of independent random variables. Their bound contains an additional factor $\log n$, and they asked whether this factor can be removed. We answer this upper-bound question affirmatively. More...

    arxiv.org/abs/2608.09870 · PDF

  2. 02

    CPDA: Class-Conditional Path Distribution Alignment for Unsupervised Time-Series Domain Adaptation

    Felix Ott, Christopher Mutschler

    stat.ML · cs.LG

    Unsupervised time-series domain adaptation (DA) addresses the challenge of transferring a classifier from a labeled source domain to an unlabeled target domain under distribution shifts induced by different users, sensors, devices, acquisition conditions, or temporal dynamics. Existing methods typically mitigate this shift by aligning marginal feature distributions through adversarial training, optimal transport, or moment-based...

    arxiv.org/abs/2608.09193 · PDF

This edition is part of The Daily Abstract — stat.ML archive. Subscribe to receive these in your inbox each morning, automatically translated to Spanish, with reply-to-PDF: arxivdaily.ignorelist.com.

Colophon Set in Georgia, with system sans for interface chrome and a monospaced stack for code and paper identifiers. Sole accent: amber #D99C5E. Built and served on an always-free VM. The masthead is set 14% letterspaced because newspapers do that and it works.