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mcyoung.xyz | ||
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www.jeremykun.com
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| | | | | The singular value decomposition (SVD) of a matrix is a fundamental tool in computer science, data analysis, and statistics. It's used for all kinds of applications from regression to prediction, to finding approximate solutions to optimization problems. In this series of two posts we'll motivate, define, compute, and use the singular value decomposition to analyze some data. (Jump to the second post) I want to spend the first post entirely on motivation and background. | |
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blog.mecheye.net
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andrea.corbellini.name
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| | | | | [AI summary] The text provides an in-depth explanation of elliptic curve cryptography (ECC), covering fundamental concepts such as elliptic curves over finite fields, point addition, cyclic subgroups, subgroup orders, and the discrete logarithm problem. It also discusses practical aspects like finding base points, cofactors, and the importance of choosing subgroups with high order for cryptographic security. The text emphasizes that ECC relies on the difficulty of solving the discrete logarithm problem on elliptic curves, which is considered computationally hard and forms the basis for secure cryptographic protocols like ECDH and ECDSA. | |
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lisyarus.github.io
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