fedjax
FedScale
| fedjax | FedScale | |
|---|---|---|
| 1 | 4 | |
| 249 | 366 | |
| 0.4% | 1.4% | |
| 4.6 | 7.9 | |
| 7 months ago | 5 months ago | |
| Python | Python | |
| Apache License 2.0 | Apache License 2.0 |
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fedjax
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[R] Google AI 0pen Sources ‘FedJAX’, A JAX-based Python Library for Federated Learning Simulations
A new google study introduces FedJAX, a JAX-based open-source library for federated learning simulations that emphasizes ease-of-use in research. FedJAX intends to construct and assess federated algorithms faster and easier for academics by providing basic building blocks for implementing federated algorithms, preloaded datasets, models, and algorithms, and fast simulation speed.
FedScale
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University of Michigan Researchers Open-Source ‘FedScale’: a Federated Learning (FL) Benchmarking Suite with Realistic Datasets and a Scalable Runtime to Enable Reproducible FL Research on Privacy-Preserving Machine Learning
Continue reading | Checkout the paper, github link
- We created the most comprehensive benchmark datasets for federated learning to date!
- The most comprehensive benchmark datasets for federated learning to date!
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The most comprehensive benchmark datasets for federated learning to date
We created FedScale, which has a diverse set of challenging and realistic benchmark datasets to facilitate scalable, comprehensive, and reproducible federated learning (FL) research. FedScale datasets are large-scale, encompassing a diverse range of important FL tasks, such as image classification, object detection, word prediction, and speech recognition. Our evaluation platform provides flexible APIs to implement new FL algorithms and includes new execution backends with minimal developer efforts. Check it out, and feel free to join the FedScale community via Slack(https://join.slack.com/t/fedscale/shared_invite/zt-uzouv5wh-ON8ONCGIzwjXwMYDC2fiKw)!
Paper: https://arxiv.org/abs/2105.11367 and Github repo: https://github.com/symbioticlab/fedscale
Cheers!
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