3 accepted papers
Vertical federated learning (VFL) is a collaborative learning scheme where clients share some overlapping samples but have different feature spaces. Existing VFL schemes are restricted in model performance and deployment feasibility due to the scarcity of overlapping labeled samples and high communi…
The Audio-Visual Video Parsing task aims to recognize events occurring in video segments for each modality. Presently, the excellent performance in handling video parsing is shown by generating pseudo labels at the segment level. However, these approaches still suffer from adequate semantic learning…
Federated learning (FL) has attracted growing attention since it allows for privacy-preserving collaborative training on decentralized clients without explicitly uploading sensitive data to the central server. However, recent works have revealed that it still has the risk of exposing private data to…