20 citations · 26 across the 2 of their papers we have counts for
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cs.LG2021★ 20 cited
FedJAX: Federated learning simulation with JAX
Jae Hun Ro, Ananda Theertha Suresh, Ke Wu
Federated learning is a machine learning technique that enables training across decentralized data. Recently, federated learning has become an active area of research due to an inc…
cs.LG2021
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…
cs.LG2020
Three Approaches for Personalization with Applications to Federated Learning
Yishay Mansour, Mehryar Mohri, Jae Ro +1
The standard objective in machine learning is to train a single model for all users. However, in many learning scenarios, such as cloud computing and federated learning, it is poss…