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Practical Federated Gradient Boosting Decision Trees
[article]
2019
arXiv
pre-print
Gradient Boosting Decision Trees (GBDTs) have become very successful in recent years, with many awards in machine learning and data mining competitions. There have been several recent studies on how to train GBDTs in the federated learning setting. In this paper, we focus on horizontal federated learning, where data samples with the same features are distributed among multiple parties. However, existing studies are not efficient or effective enough for practical use. They suffer either from the
arXiv:1911.04206v2
fatcat:ccasyn6lorg3ddnwn73jjywmxi