Linking pages
Linked pages
- https://snips.ai/ 146 comments
- Data Version Control · DVC https://dvc.org/ 123 comments
- Federated Learning: Collaborative Machine Learning without Centralized Training Data – Google AI Blog https://ai.googleblog.com/2017/04/federated-learning-collaborative.html 33 comments
- Flower: A Friendly Federated Learning Framework https://flower.dev/ 13 comments
- https://arxiv.org/pdf/1602.05629.pdf 6 comments
- Federated Learning with Formal Differential Privacy Guarantees – Google AI Blog https://ai.googleblog.com/2022/02/federated-learning-with-formal.html 3 comments
- [1811.04017] A generic framework for privacy preserving deep learning https://arxiv.org/abs/1811.04017 1 comment
- Continuous Delivery for Machine Learning https://martinfowler.com/articles/cd4ml.html#PlatformThinking 0 comments
- XayNet | Open Source Federated Learning Framework for Edge AI https://xaynet.webflow.io/ 0 comments
- OpenMined http://openmined.org 0 comments
- GitHub - OpenMined/PySyft: data science on data without acquiring a copy https://github.com/OpenMined/PySyft 0 comments
- [1802.09941] Demystifying Parallel and Distributed Deep Learning: An In-Depth Concurrency Analysis https://arxiv.org/abs/1802.09941 0 comments
- [1807.00459] How To Backdoor Federated Learning https://arxiv.org/abs/1807.00459 0 comments
- Applying Differential Privacy to Large Scale Image Classification – Google AI Blog https://ai.googleblog.com/2022/02/applying-differential-privacy-to-large.html 0 comments
- Datafleets https://www.datafleets.com/ 0 comments
- [1812.00984] Protection Against Reconstruction and Its Applications in Private Federated Learning https://arxiv.org/abs/1812.00984 0 comments
- Xayn Personalisation Engine for News Providers https://www.xayn.com/ 0 comments
- [1902.01046] Towards Federated Learning at Scale: System Design https://arxiv.org/abs/1902.01046 0 comments
- [1702.07464] Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning https://arxiv.org/abs/1702.07464 0 comments
- [1902.04885] Federated Machine Learning: Concept and Applications https://arxiv.org/abs/1902.04885 0 comments
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