2 citations · 2 across the 1 of their papers we have counts for
2 papers
cs.LG2021
Precision-Weighted Federated Learning
Jonatan Reyes, Lisa Di Jorio, Cecile Low-Kam +1
Federated Learning using the Federated Averaging algorithm has shown great advantages for large-scale applications that rely on collaborative learning, especially when the training…
stat.ML2018★ 2 cited
Adversarially Learned Mixture Model
Andrew Jesson, Cécile Low-Kam, Tanya Nair +3
The Adversarially Learned Mixture Model (AMM) is a generative model for unsupervised or semi-supervised data clustering. The AMM is the first adversarially optimized method to mode…