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Áine Cahill

2 accepted papers

2024

$\texttt{pfl-research}$: simulation framework for accelerating research in Private Federated Learning

NeurIPS 2024poster

Federated learning (FL) is an emerging machine learning (ML) training paradigm where clients own their data and collaborate to train a global model, without revealing any data to the server and other participants. Researchers commonly perform experiments in a simulation environment to quickly iterat…

Cited by 2SourcePDFScholar
2024

Improved Modelling of Federated Datasets using Mixtures-of-Dirichlet-Multinomials

ICML 2024poster

In practice, training using federated learning can be orders of magnitude slower than standard centralized training. This severely limits the amount of experimentation and tuning that can be done, making it challenging to obtain good performance on a given task. Server-side proxy data can be used to…