May 18, 2020 · In this paper, we aim to build large-scale secure XGB under vertically federated learning setting. We guarantee data privacy from three aspects.
Oct 30, 2021 · In this paper, we aim to build large-scale secure XGB under vertically federated learning setting. We guarantee data privacy from three aspects.
Sep 2, 2021 · In this paper, we aim to build large- scale secure XGB under vertically federated learning setting. We guarantee data privacy from three aspects ...
This paper aims to build large-scale secure XGB under vertically federated learning setting, and guarantees data privacy from three aspects, and proposes ...
Jun 5, 2024 · One of the SS-based vertical federated tree algorithms is [49] , which adopts SS to train secure GBDT with data vertically partitioned to ...
Large-Scale Secure XGB for Vertical Federated Learning ... Privacy-preserving machine learning has drawn increasingly attention recently, especially with kinds of ...
We propose EVFeX, an efficient vertical federated XGBoost algorithm based on optimized secure matrix multiplication, which eliminates the need for time- ...
To address these issues, we propose an efficient and privacy-preserving vertical federated learning framework based on the XGBoost algorithm, namely ELXGB, ...
Dec 18, 2024 · The secure federated algorithms, both horizontal and vertical, are implemented and added to the federated schemes supported by XGBoost library, ...
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Jun 28, 2024 · XGBoost is a highly effective and scalable machine learning algorithm widely employed for regression, classification, and ranking tasks.