Gradient-less Federated Gradient Boosting Trees with Learnable Learning Rates

arXiv:2304.07537v3 Announce Type: replace
Abstract: The privacy-sensitive nature of decentralized datasets and the robustness of eXtreme Gradient Boosting (XGBoost) on tabular data raise the needs to train XGBoost in the context of federated learning (FL). Existing works on federated XGBoost in the horizontal setting rely on the sharing of gradients, which induce per-node level communication frequency and serious privacy concerns. To alleviate these problems, we develop an innovative framework for horizontal federated XGBoost which does not depend on the sharing …

arxiv boosting cs.ai cs.dc cs.ds cs.lg gradient trees type