Questions tagged [federated-learning]
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How does Knowledge Distillation help Federated Learning?
As per my understanding, typically in FL, there is a global server that interacts with various client devices. The global server and the client both possess a ML models. The client(s) update their ...
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What is the difference between the definition of "accuracy" in machine learning and federated learning?
What is the difference between the definition of "accuracy" in machine learning and federated learning?
In particular, how is the accuracy calculated in the following paper:
Cai, Lingshuang,...
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What is dynamic data sampling in federated learning?
I am trying to learn about Federated Learning (FL), but I have a question.
What is dynamic data sampling in FL?
Cai, Lingshuang, et al. "Dynamic Sample Selection for Federated Learning with ...
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How would the performance of federated learning compare to the performance of centralized machine learning when the data is i.i.d.?
How would the performance of federated learning (FL) compare to the performance of centralized machine learning (ML), when the data is independent and identically distributed (i.i.d.)?
Moreover, what ...
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What is Federated Learning?
How would you explain Federated Learning in simple layman terms for a non-STEM person?
What are the main ideas behind Federated Learning?
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How to express a fully connected neural network succintly using linear algebra?
I'm currently reading the paper Federated Learning with Matched Averaging (2020), where the authors claim:
A basic fully connected (FC) NN can be formulated as: $\hat{y} = \sigma(xW_1)W_2$ [...]
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What is the difference between edge computing and federated learning?
I recently read about federated learning introduced by Google, but it seems to be like edge computing.
What is the difference between edge computing and federated learning?
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