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# FedAUX
* **Title:** FEDAUX: Leveraging Unlabeled Auxiliary Data in Federated Learning
* **Venue:** IEEE TNNLS 2021
* **Link to paper:** https://ieeexplore.ieee.org/document/9632275
## Do you want …
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### Describe the bug
I've used `start_simulation` to simulate a federated learning task on MNIST and run the script on a Ubuntu machine with 6 GPUs, 24 GB each (see the first image below). I realiz…
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### Describe the bug
when testing the jetson nano example(https://github.com/adap/flower/tree/main/examples/embedded_devices) and run the
$ ./run_jetson.sh --server_address= --cid=0 --model=ResNe…
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Dear,
First thank you for your code.
I have run your code, however, the result is not satisfying.
Result:
Training accuracy: 43.00
Testing accuracy: 43.00
## my cmd:
> python main_fed.py --d…
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Splitting this out from the unrelated issue:
> Not sure if the implementation/etc would be compatible, but here's another distributed StableDiffusion training project a friend recently linked…
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Hi Y'all,
This project is really cool, but it should also support decision trees due to their popularity and applications. I would like to contribute a working XGboost implementation.
However, th…
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### What is your question?
## How to Pass Weights as Parameters in Flower?
I’m trying to use the Flower framework to train a YOLO model in a federated learning setting. I’m having trouble figuring…
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Hi @danieljanes,
I am using flower on android and I noticed that the flower server doesn't send the android clients the model instead the model is pre-built on the client device. How to resolve th…
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Could you add more servers in FedAvg for faster training speed?
As the BytePS does.