Browsing University of Waterloo by Subject "federated learning"
Now showing items 1-3 of 3
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Bayesian Federated Learning in Predictive Space
(University of Waterloo, 2023-08-10)Federated Learning (FL) involves training a model over a dataset distributed among clients, with the constraint that each client's data is private. This paradigm is useful in settings where different entities own different ... -
Differentially-private Multiparty Clustering
(University of Waterloo, 2023-09-13)In an era marked by the widespread application of Machine Learning (ML) across diverse domains, the necessity of privacy-preserving techniques has become paramount. The Euclidean k-Means problem, a fundamental component ... -
Learn Privacy-friendly Global Gaussian Processes in Federated Learning
(University of Waterloo, 2022-08-17)In the era of big data, Federated Learning (FL) has drawn great attention as it naturally operates on distributed computational resources without the need of data warehousing. Similar to Distributed Learning (DL), FL ...