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jeremykun.com | ||
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thenumb.at
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| | | | | [AI summary] This text provides a comprehensive overview of differentiable programming, focusing on its application in machine learning and image processing. It explains the fundamentals of automatic differentiation, including forward and backward passes, and demonstrates how to implement these concepts in a custom framework. The text also discusses higher-order differentiation and its implementation in frameworks like JAX and PyTorch. A practical example is given using differentiable programming to de-blur an image, showcasing how optimization techniques like gradient descent can be applied to solve real-world problems. The text emphasizes the importance of differentiable programming in enabling efficient and flexible computation for various domains, includ... | |
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jeremykun.wordpress.com
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| | | | | The Learning With Errors problem is the basis of a few cryptosystems, and a foundation for many fully homomorphic encryption (FHE) schemes. In this article I'll describe a technique used in some of these schemes called modulus switching. In brief, an LWE sample is a vector of values in $\mathbb{Z}/q\mathbb{Z}$ for some $q$, and in... | |
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www.ayoub-benaissa.com
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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. | |
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www.latacora.com
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| | | When people talk about PBKDFs (Password Based Key Derivation Functions), this is usually either in the context of secure password storage, or in the context of how to derive cryptographic keys from potentially low-entropy passwords. The Password Hashing Competition (PHC, 2013-2015) was an open competition to derive new password hashing algorithms, resulting in Argon2 hash as its winner. Apart from achieving general hash security, many of the candidates focused on achieving resistance to parallel attacks ... | ||
