no code implementations • ICLR 2020 • Jeffrey Li, Mikhail Khodak, Sebastian Caldas, Ameet Talwalkar
Parameter-transfer is a well-known and versatile approach for meta-learning, with applications including few-shot learning, federated learning, and reinforcement learning.
1 code implementation • ICLR 2019 • Sebastian Caldas, Jakub Konečny, H. Brendan McMahan, Ameet Talwalkar
Communication on heterogeneous edge networks is a fundamental bottleneck in Federated Learning (FL), restricting both model capacity and user participation.
7 code implementations • 3 Dec 2018 • Sebastian Caldas, Sai Meher Karthik Duddu, Peter Wu, Tian Li, Jakub Konečný, H. Brendan McMahan, Virginia Smith, Ameet Talwalkar
Modern federated networks, such as those comprised of wearable devices, mobile phones, or autonomous vehicles, generate massive amounts of data each day.