{
  "id": 563,
  "url": "https://arxiv.org/abs/2606.26975v1",
  "title": "XMSE-Aware Adaptive Empirical Bayes Estimation",
  "summary": "Empirical Bayes (EB) estimators can match the first-order asymptotic risk of maximum likelihood (ML) while behaving very differently at second order: recent excess mean squared error (XMSE) analysis shows that kernel-based EB estimation may be worse than ML when the kernel is poorly aligned with the true parameter. This paper turns that diagnostic into a design principle. We propose an XMSE-aware mixed estimator that interpolates between ML and EB shrinkage. Its fixed-weight XMSE is a scalar qua",
  "authors": "Minghao Chen, Jiale Zheng",
  "category": "research",
  "topics": "healthcare",
  "orgs": null,
  "regions": null,
  "published_at": "2026-06-25T12:47:41.000Z",
  "fetched_at": "2026-07-14T14:14:37.248Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/563",
  "original_url": "https://arxiv.org/abs/2606.26975v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}