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www.jeremykun.com
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| | [AI summary] The text discusses the implementation of homomorphic operations in the context of RLWE (Ring Learning With Errors) and GSW (Gentry-Sahai-Waters) encryption schemes. Key concepts include the use of encryptions of zero to facilitate homomorphic multiplication, the structure of GSW ciphertexts as matrices of RLWE ciphertexts, and the role of scaling factors to manage error growth during multiplication. The main goal is to enable secure computation of polynomial products without revealing the underlying plaintexts.
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| | This is the first of a series of blog posts about the use of homomorphic encryption for deep learning. Here I introduce the basics and terminology as well as link to external resources that might help with a deeper understanding of the topic.
| | jeremykun.com
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| | In this article I'll derive a trick used in FHE called sample extraction. In brief, it allows one to partially convert a ciphertext in the Ring Learning With Errors (RLWE) scheme to the Learning With Errors (LWE) scheme. Here are some other articles I've written about other FHE building blocks, though they are not prerequisites...
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| Clearly This is a Metaphor For Something