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Weiqi Liu

2 accepted papers

2025

MARS-VFL: A Unified Benchmark for Vertical Federated Learning with Realistic Evaluation

NeurIPS 2025spotlight

Vertical Federated Learning (VFL) has emerged as a critical privacy-preserving learning paradigm, enabling collaborative model training by leveraging distributed features across clients. However, due to privacy concerns, there are few publicly available real-world datasets for evaluating VFL methods…

Cited by 0SourceScholar
2022

Memory-Based Message Passing: Decoupling the Message for Propagation from Discrimination

ICASSP 2022accepted

Message passing is a fundamental procedure for graph neural networks in the field of graph representation learning. Based on the homophily assumption, the current message passing always aggregates features of connected nodes, such as the graph Laplacian smoothing process. However, real-world graphs…

Cited by 0SourceScholar