no code implementations • 7 Mar 2024 • Gyudong Kim, Mehdi Ghasemi, Soroush Heidari, Seungryong Kim, Young Geun Kim, Sarma Vrudhula, Carole-Jean Wu
Such fragmentation introduces a new type of data heterogeneity in FL, namely \textit{system-induced data heterogeneity}, as each device generates distinct data depending on its hardware and software configurations.
no code implementations • 30 Nov 2022 • Young Geun Kim, Carole-Jean Wu
Federated learning (FL) has emerged as a solution to deal with the risk of privacy leaks in machine learning training.
no code implementations • 16 Jul 2021 • Young Geun Kim, Carole-Jean Wu
Federated learning enables a cluster of decentralized mobile devices at the edge to collaboratively train a shared machine learning model, while keeping all the raw training samples on device.
no code implementations • 6 May 2020 • Young Geun Kim, Carole-Jean Wu
Such execution scaling decision becomes more complicated with the stochastic nature of mobile-cloud execution, where signal strength variations of the wireless networks and resource interference can significantly affect real-time inference performance and system energy efficiency.