Questions tagged [federated-learning]

For questions regarding Federated Learning, a machine learning technique that trains an algorithm across multiple decentralized edge devices or servers holding local data samples, without exchanging them

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Averaging Weights of Identical LSTM Models for a Unified Global Model

I'm currently working on a project where I have several pre-trained LSTM models, all with the same architecture. My goal is to combine these models into a single global model by averaging their ...
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Can we use the word "federated learning" for non-machine learning solutions?

My question is can we use "learning" when we don't employ deep learning or a ML model but simply "learning" from the data using basic statistics?
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Benchmark dataset with both images and tabular data

In the medical sector, there are situations in which an image dataset is associated with a tabular dataset containing different features but the same labels as the image dataset. For example, suppose ...
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Proof that averaging weights is equal to averaging gradients (FedSGD vs FedAvg)

The first paper of Federated Learning "Communication-Efficient Learning of Deep Networks from Decentralized Data" presents FedSGD and FedAvg. In Federated Learning the learning task is ...
CasellaJr's user avatar
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How to compute the mean of weights of multiple models?

Hi i'm a student and i'm working on a Federated Learning problem, but before doing that with the proper tools like OpenFL or Flower, I started a little experiment to try in local to train using this ...
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Accuracy over 100%

I am using OpenFL, the Intel framework for Federated Learning. If I run their tutorial example, I have that loss decreases and accuracy is in range 0-100%, like this: ...
CasellaJr's user avatar
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tnn architecture suitable for distributed learning?

I am working on tnn, i found that its not working like other neural networks like they have layers and weights. my question is that tnn can be used with federated learning in which we trained model ...
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Dividing a dataset to parallelize machine learning training on the cloud

I'm very new to machine learning. I am doing a project for a subject called parallel and distributed computing, in which we have to speed up a heavy computation using parallelism or distributed ...
ptushev's user avatar
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Right Package for Federated Learning

Could Someone list the pros and cons with respect to using federated learning with the following packages: TensorFlow federated PySyft Are there certain tasks which are specific to either or is one ...
Academic's user avatar
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