Logistic Regression (LR) is the most widely used machine learning model in industry for its
efficiency, robustness, and interpretability. Due to the problem of data isolation and the …

XGBoost is one of the most widely used machine learning models in the industry due to its
superior learning accuracy and efficiency. Targeting at data isolation issues in the big data …

Abstract Knowledge Graph (KG) has attracted more and more companies' attention for its
ability to connect different types of data in meaningful ways and support rich data services …

Federated Learning (FL) is an approach to collaboratively train a model across multiple
parties without sharing data between parties or an aggregator. It is used both in the …

Tree-based models are among the most efficient machine learning techniques for data
mining nowadays due to their accuracy, interpretability, and simplicity. The recent …

We present a novel protocol XORBoost for both training gradient boosted tree models and
for using these models for inference in the multiparty computation (MPC) setting. Our …

Secret sharing allows a dealer to distribute a secret among a set of parties such that only
authorized subsets, specified by an access structure, can reconstruct the secret. Sehrawat …

Tree-based models are wildly adopted in various real-world scenarios. Recently, there is a
growing interest in vertical federated tree-based model learning to build tree-based models …

Federated learning (FL) is the distributed machine learning framework that enables
collaborative training across multiple parties while ensuring data privacy. Practical …

Abstract Many Federated Learning algorithms have been focused on linear models, kernel-
based, and neural-network-based models. However, recent interest in tree-based models …