mlsanityData to 14 Oct 2026

TF Boosted Trees: A scalable TensorFlow based framework for gradient boosting

arXiv 1710.11555 ↗First posted 31 Oct 2017stat.ML cs.LGcited by 1

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Abstract (arXiv)

TF Boosted Trees (TFBT) is a new open-sourced frame-work for the distributed training of gradient boosted trees. It is based on TensorFlow, and its distinguishing features include a novel architecture, automatic loss differentiation, layer-by-layer boosting that results in smaller ensembles and faster prediction, principled multi-class handling, and a number of regularization techniques to prevent overfitting.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 31 Oct 2017.

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