Overcoming Forgetting, in Federated Learning on Non-IID Data.
We tackle the problem of Federated Learning in the non i.i.d. case, in which local models drift apart, inhibiting learning.
Overcoming Forgetting in Federated Learning on Non-IID Data.
We tackle the problem of Federated Learning in the non i.i.d. case, in which local models drift apart, inhibiting learning.
Distributed training on edge devices: Batch Normalisation.
An Edgify Research Team Publication. In the first post of this series, we presented two basic approaches to distributed…
Distributed Training on Edge Devices. Large Batch vs. Federated Learning.
An Edgify Research Team Publication, this is the first, introductory post, in our three-part algorithmic series on real-world distributed training.
Distributed Training on Edge Devices: Communication compression.
An Edgify.ai Research Team Publication. In the first post of this series, we presented two basic approaches to distributed training on edge…