Vertical Federated Learning (VFL) is a federated learning setting where multiple parties with
different features about the same set of users jointly train machine learning models without …

Vertical Federated Learning (VFL) enables an active party with labeled data to enhance
model performance (utility) by collaborating with multiple passive parties that possess …

Vertical Federated Learning (VFL) has emerged as a collaborative training paradigm that
allows participants with different features of the same group of users to accomplish …

As necessary information about whether cooperation can be reached, rewards should be
determined in advance in Vertical Federated Learning (VFL). To determine reasonable …

Machine learning (ML) models trained on datasets owned by different organizations and
physically located in remote databases offer benefits in many real-world use cases. State …