Comments (4)
MiKKiYang
commented on April 28, 2024
@joneswong wish your reply
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joneswong
commented on April 28, 2024
@joneswong wish your reply
Thanks for your attention. I have assigned this thread to @xieyxclack . Let's discuss together
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xieyxclack
commented on April 28, 2024
Thanks a lot for your interest!
- FederatedScope provides the ModelZoo and AlgoZoo for convenient usage. And more models and algos are coming soon :)
- FederatedScope adopts an event-driven architecture for flexibly and conveniently describing asynchronous federated learning with heterogeneous information exchanging, which frames an FL course into event-handler pairs. Please refer to our paper for more details about the characteristics and advantages of FederatedScope.
- We are working on some internal real-world FL applications. And we have released the source code of FederatedScope for the public and welcome users to deploy the real-world FL application with FederatedScope.
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xieyxclack
commented on April 28, 2024
Hope that helps! This thread is closed and let us know if you have more questions.
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Related Issues (20)
- Confusing range of patience
- To allow specifying respective data transformations for different splits
- Would unsupported operator affect training HOT 2
- Is transformation of data ignored? HOT 1
- Inappropriate output order
- Client-wise configurations are ignored
- Enable empty split
- To conduct federated domain generalization
- [Discussion] Refactor worker class
- Issue with starting a FL process with a trained model HOT 10
- private set intersection HOT 1
- Cannot run fl training on Femnist in distribute mode HOT 1
- Message asked for local pretraining is missing the "content" para when train a graph model in distributed mode? HOT 1
- Cannot run fl training on cora in distributed mode HOT 4
- Inappropriate way of assigning values to Client data in toy and vfl synthetic dataset HOT 2
- Failed to get the results when using WandB in vFL HOT 1
- Drawbacks facing graph federated learning in the setting of traffic speed prediction HOT 1
- How to start with my own dataset and the given examples? HOT 1
- Seeking Flat Minima
- Regarding GeneralTorchTrainer HOT 4
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