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qchu.wordpress.com | ||
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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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almostsuremath.com
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| | | | | Given a sequence $latex {X_1,X_2,\ldots}&fg=000000$ of real-valued random variables defined on a probability space $latex {(\Omega,\mathcal F,{\mathbb P})}&fg=000000$, it is a standard result that the supremum $latex \displaystyle \setlength\arraycolsep{2pt} \begin{array}{rl} &\displaystyle X\colon\Omega\rightarrow{\mathbb R}\cup\{\infty\},\smallskip\\ &\displaystyle X(\omega)=\sup_nX_n(\omega). \end{array} &fg=000000$ is measurable. To ensure that this is well-defined, we need to allow X to have values in $latex... | |
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cp4space.hatsya.com
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| | | | | In the early 1930s, Pascual Jordan attempted to formalise the algebraic properties of Hermitian matrices. In particular: Hermitian matrices form a real vector space: we can add and subtract Hermitian matrices, and multiply them by real scalars. That is to say, if $latex \lambda, \mu \in \mathbb{R}$ and $latex A, B$ are Hermitian matrices, then... | |
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www.jeremymorgan.com
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| | | Want to learn about PyTorch? Of course you do. This tutorial covers PyTorch basics, creating a simple neural network, and applying it to classify handwritten digits. | ||
