3 accepted papers
The holy grail of machine learning is to enable Continual Federated Learning (CFL) to enhance the efficiency, privacy, and scalability of AI systems while learning from streaming data. The primary challenge of a CFL system is to overcome global catastrophic forgetting, wherein the accuracy of the gl…
The integration of Artificial Intelligence into wireless networks is rapidly advancing, with Federated Learning (FL) at the forefront as the preserving privacy strategy that enables learning on edge devices. Over-The-Air FL (OTA-FL) harnesses Multiple Access Channels (MACs) for efficient, low-latenc…
The use of AI has led to the era of pervasive intelligence, marked by a proliferation of smart devices in our daily lives. Federated Learning (FL) enables machine learning at the edge without having to share user-specific private data with an untrusted third party. Conventional FL techniques are sup…