TF Boosted Trees: A scalable TensorFlow based framework for gradient boosting
Not on the map. Why?
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.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2022: 1.
1 paper.