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Does Pyfhel support Batching Encode and Bootstrapping? #237
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Here are just few examples of issues asking about bootstrapping: #216, #204, #144, #136 -> "SEAL does not provide this out of the box, meaning that Pyfhel is limited to SHE until it is merged to the bootstrapping of OpenFHE." I saw also a comment about "batch encoding" here that Pyfhel already uses batch encoding by default. But TBH now I couldn't recall how 😄 |
Thanks for your support. I'm trying to implement BFV bootstrapping, but it's too hard 😢 |
You can use OpenFHE written in C++ that has already implemented bootstrapping; however it is very slow compared to Pyfhel. |
I want to implement logistic regression with BFV scheme but cannot find any public code to reference. Do you know any document or source code about this topic? :'( |
I know about a library Concrete ML that has ML models including Linear (regression) but with TFHE scheme implemented. Let me search a bit about BFV and I'll come back to you soon. |
I found these resources just by having a quick look but you can continue by searching among Google scholar papers and project in GitHub (putting #homomorphic-encryption and #logistic-regression): Papers (if they don't have public access to the code; you can still ask their authors):
Projects (I'm not sure they have implemented the bootstrapping of BFV but maybe good for you to look at them):
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I have read those papers and github code. However, most of them use CKKS or don't have source code for me to reference. Anyway, thank you very much :(( |
Ah, and why so far you want to use BFV? I guess the conversion shouldn't be difficult. TBH, I'm not sure for the current version of Pyfhel but for instance for 3.1.4, once Alberto told me that I need to rewrite things a bit e.g., turn np.sum into sums and rotations to have this conversion between schemes. |
Ah, I use BFV due to the requirements of my course project. There are many difficulties when using this scheme compared to CKKS :D |
Please let me know if Pyfhel support Batching Encode and Bootstrapping?
Thank you so much.
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