{
  "id": 509970,
  "title": "Forking-Sequences — Part II: Multi-Horizon Forecast Ensembling with Reduced Volatility",
  "url": "https://urgent.news/2026/08/10/forking-sequences-part-ii-multi-horizon-forecast-ensembling-with",
  "topic": "ai",
  "section": "AI",
  "published": "2026-08-10T21:52:23.000Z",
  "source": {
    "name": "Machine Learning @ CMU",
    "slug": "machine-learning-cmu",
    "url": "https://blog.ml.cmu.edu/2026/08/10/forking-sequences-part-ii-multi-horizon-forecast-ensembling-with-reduced-volatility/"
  },
  "original_language": "en",
  "account": null,
  "summary": "Based on: Potosnak, W., Wolff, M., Cao, M., Ma, R., Konstantinova, T., Efimov, D., Mahoney, M.W., Oreshkin, B., & Olivares, K.G. \"Forking-Sequences: Statistically and Computationally Efficient Multi-Horizon Forecasting with Reduced Volatility.\" Transactions on Machine Learning Research, 2026. (Disclaimer: Code implementation not used in the paper; not affiliated with Amazon — provided as a…",
  "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."
}