104 citations · 189 across the 14 of their papers we have counts for
3 papers · 1 filter
Efficient and Private Federated Learning with Partially Trainable Networks
Hakim Sidahmed, Zheng Xu, Ankush Garg +2
Federated learning is used for decentralized training of machine learning models on a large number (millions) of edge mobile devices. It is challenging because mobile devices often…
Position-Invariant Truecasing with a Word-and-Character Hierarchical Recurrent Neural Network
Hao Zhang, You-Chi Cheng, Shankar Kumar +2
Truecasing is the task of restoring the correct case (uppercase or lowercase) of noisy text generated either by an automatic system for speech recognition or machine translation or…
Communication-Efficient Agnostic Federated Averaging
Jae Ro, Mingqing Chen, Rajiv Mathews +2
In distributed learning settings such as federated learning, the training algorithm can be potentially biased towards different clients. Mohri et al. (2019) proposed a domain-agnos…