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Prepare presentation materials (in many cases: update and review existing notebook)
- [x] "download" button for `.ipynb` version of tutorials
- [x] [ML] Introduction to Federated Learning
- [x] [SC]…
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Hi,
Thank you very much for your code.
Is it possible to run this code on Google Colab?
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**Is your feature request related to a problem? Please describe.**
Currently there is only one implementation of local differential privacy (LDP): RAPPOR[1], implemented in https://github.com/TL-Syst…
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Zero-knowledge proofs have an important role to play in the future of verified machine learning prediction. However, no deep learning framework has the ability to perform verified computation of neura…
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Dear people from Flower,
Would it be possible for you create an example with Pytorch Lightning.
Reasons: Pytorch Lightning is an advanced Training and I wonder how it could be leveraged from Fed…
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I am trying to reproduce the director-envoy notebook on DevCloud for a demo. There is a strange behavior that I have come across. One of the envoy starts training, but other one fails for some reason.…
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Hi, I read your paper and code, and this work has inspired me a lot in my work on Federated Learning Optimization. I am trying to reproduce FedProx using PyTorch and I am confused on a small detail. …
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When I was running the code federatedMR_main.py, it appeared IndexError: tuple index out of range.
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There are `OptimizerConstructor` ..., but why not provide a runner constructor?
It would be more general and flexible to implement some functions.
Looking forward it.
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As described in the README, "CrypTen is a framework for Privacy Preserving Machine Learning built on PyTorch."
One question that confuses me is，what is the difference between **Privacy Preserving …