<?xml version="1.0" encoding="UTF-8"?><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/"><dc:title>xgboost-a-scalable-tree-boosting-system-2023-021</dc:title><dc:creator>Tianqi Chen, Carlos Guestrin</dc:creator><dc:date>2023</dc:date><dc:description>This record links to the XGBoost paper, which describes a scalable tree boosting system used widely in data science. It provides a strong test case for statistics metadata, predictive modelling keywords, and external link previews.</dc:description><dc:identifier>https://inrepscholar.com/projects/960</dc:identifier></oai_dc:dc>