Vertical federated learning (VFL) is a distributed machine learning paradigm that
collaboratively trains models using passive parties with features and an active party with …

SecureBoost is a tree-boosting algorithm that leverages homomorphic encryption (HE) to
protect data privacy in vertical federated learning. SecureBoost and its variants have been …

SecureBoost is a tree-boosting algorithm leveraging homomorphic encryption to protect data
privacy in vertical federated learning setting. It is widely used in fields such as finance and …

Split learning has emerged as a practical and efficient privacy-preserving distributed
machine learning paradigm. Understanding the privacy risks of split learning is critical for its …

As a privacy-preserving method for implementing Vertical Federated Learning, Split
Learning has been extensively researched. However, numerous studies have indicated that …

Split learning is a promising paradigm for privacy-preserving distributed learning. The
learning model can be cut into multiple portions to be collaboratively trained at the …

Neural Radiance Fields (NeRF) have revolutionized 3D computer vision and graphics,
facilitating novel view synthesis and influencing sectors like extended reality and e …