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Published on: 2025-03-06 15:26:31 Published on: 2025-03-06 15:26:31

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Earn bonus returns through promoting products ✌️【Interview】✌️₹500 to start, high returns to earn. Join now and watch your wealth increase!NVIDIA introduces CUDA-accelerated homomorphic encryption in Federated XGBoost, enhancing data privacy and efficiency in federated learning.

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Earn bonus returns through promoting products ✌️【Interview】✌️Low-risk, high-reward investments starting from ₹500. Begin today!This development aims to address security concerns in both horizontal and vertical federated learning collaborations, according toNVIDIA.XGBoost, a widely used machine learning algorithm for tabular data modeling, has been extended by NVIDIA to support multisite collaborative training through Federated XGBoost.

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In vertical federated learning, parties hold different features of a dataset, while in horizontal settings, each party holds all features for a subset of the population.NVIDIA FLARE, an open-source SDK, supports this federated learning framework by managing communication challenges and ensuring seamless operation across various network conditions.

Federated XGBoost operates under an assumption of full mutual trust, but NVIDIA acknowledges that in practice, participants may attempt to glean additional information from the data, necessitating enhanced security measures.To mitigate potential data leaks, NVIDIA has integrated homomorphic encryption (HE) into Federated XGBoost.

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