Quoc‐Viet Pham

MCNet: An Efficient CNN Architecture for Robust Automatic Modulation Classification

2020 · IEEE Communications Letters

This letter proposes a cost-efficient convolutional neural network (CNN) for robust automatic modulation classification (AMC) deployed for cognitive radio services of modern communication systems. The network architecture is designed with several specific convolutional blocks to …

ToFU: Transforming How Federated Learning Systems Forget User Data

2025 · arXiv (Cornell University)

Neural networks unintentionally memorize training data, creating privacy risks in federated learning (FL) systems, such as inference and reconstruction attacks on sensitive data. To mitigate these risks and to comply with privacy regulations, Federated Unlearning …