TS-075588 — As federated learning expands across IoT, industrial, automotive, and connected-device ecosystems, maintaining reliable model training on energy-constrained edge devices remains a major challenge. Many devices operate on limited batteries or intermittent harvested energy, making continuous partici…

TS-073841 — Current federated learning (FL) systems face significant challenges in efficiently aggregating model updates over wireless networks, especially in environments with diverse data and varying channel conditions. There is a critical need for a solution that enhances bandwidth efficiency, personalizat…