Academics 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. […] Read More
Academics 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. […] Read More
White Paper 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 on […] Read More
White Paper Distributed training on edge devices: Batch Normalization with Non-IID data an Edgify Research Team Publication In the first post of this series, we presented two basic approaches to distributed training on edge devices. In […] Read More
White Paper 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 […] Read More
