20 citations · 29 across the 3 of their papers we have counts for
3 papers
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.LG2020★ 6 cited
A Theory of Multiple-Source Adaptation with Limited Target Labeled Data
Yishay Mansour, Mehryar Mohri, Jae Ro +2
We present a theoretical and algorithmic study of the multiple-source domain adaptation problem in the common scenario where the learner has access only to a limited amount of labe…
cs.LG2016★ 3 cited
Node-By-Node Greedy Deep Learning for Interpretable Features
Ke Wu, Malik Magdon-Ismail
Multilayer networks have seen a resurgence under the umbrella of deep learning. Current deep learning algorithms train the layers of the network sequentially, improving algorithmic…