{
  "id": 6702079,
  "title": "General Quantification of Covariate and Concept Shifts",
  "url": "https://urgent.news/2026/09/10/general-quantification-of-covariate-and-concept-shifts",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-10T17:57:52.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2609.11918v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Generalization under distribution shift remains a core challenge in modern machine learning, yet existing learning bound theory is limited to narrow, idealized settings and is non-estimable from samples. In this paper, we bridge the gap between theory and practical applications. We first show that existing definition of concept shift breaks when the source and target supports mismatch. Leveraging…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}