stat.ML · 2026-08-21 · No. 91

Machine Learning, 2026-08-21.

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

    Transfer Learning in Nonparametric Regression with Deep ReLU Networks

    Junpeng Ren, Carlos Misael Madrid Padilla, Yanzhen Chen, Oscar Hernan Madrid Padilla

    stat.ML · cs.LG · stat.ME

    This paper develops a general transfer learning framework for nonparametric regression with data consisting of multiple groups. Under the assumption that groups share a common structure along with group-specific deviations in additive form, the proposed method employs a two-stage offset learning procedure: the first stage pools data from all groups to estimate an overall mean function, and the second stage estimates offsets for each group,...

    arxiv.org/abs/2608.20255 · PDF

  2. 02

    Discrete Diffusion Inference-Time Control with Nested Sequential Monte Carlo

    Lohithsai Yadala Chanchu, Hany Abdulsamad, Christian A. Naesseth

    stat.ML · cs.LG

    We study inference-time control for text generation in discrete diffusion language models, where the goal is to steer sampling toward sequence-level rewards without retraining. Prior work in this domain has focused on particle-based methods such as best-of-$n$ sampling and bootstrap sequential Monte Carlo, which may suffer from overoptimism and weight degeneracy, respectively. We address these limitations using \emph{nested} sequential Monte...

    arxiv.org/abs/2608.20123 · PDF

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