3 accepted papers
Personalized federated learning (PFL) creates client-specific models to handle data heterogeneity. Previously, PFL has been shown to be naturally resistant to backdoor attack propagation across clients. In this work, we reveal that PFL remains vulnerable to backdoor attacks through a novel frequency…
Multi-agent collaborative perception (CP) improves scene understanding by sharing information across connected agents such as autonomous vehicles, unmanned aerial vehicles, and robots. Communication bandwidth, however, constrains scalability. We present ReVQom, a learned feature codec that preserves…
Accurate prediction of pedestrian trajectories is crucial as autonomous vehicles become more prevalent on roads. The dynamic nature of urban environments and the less predictable behavior of pedestrians present significant challenges in developing reliable prediction models. Earlier methods relying