Shao‐Lun Huang

Live Gradient Compensation for Evading Stragglers in Distributed Learning

2021

The training efficiency of distributed learning systems is vulnerable to stragglers, namely, those slow worker nodes. A naive strategy is performing the distributed learning by incor-porating the fastest K workers and ignoring these stragglers, which …

Personalized Federated Learning with Feature Alignment and Classifier Collaboration

2023 · arXiv (Cornell University)

Data heterogeneity is one of the most challenging issues in federated learning, which motivates a variety of approaches to learn personalized models for participating clients. One such approach in deep neural networks based tasks is …

AdaForensics: Learning A Characteristic-aware Adaptive Deepfake Detector

2024

In this paper, we propose a characteristic-aware adaptive network named AdaForensics for deepfake detection. Most existing methods learn a fixed network to detect deepfakes based on carefully-designed network architectures. However, these methods employ the same …