Federated Learning for Resource Constrained Devices
As resource constrained edge devices become increasingly more powerful, they are able to provide a larger quantity of higher quality data. However, as these devices are decentralized, it becomes difficult to gain insights from multiple devices at the same time. Federated learning allows us to learn...
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Format: | Thesis |
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Massachusetts Institute of Technology
2022
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Online Access: | https://hdl.handle.net/1721.1/144688 |