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xorshammer.com | ||
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lucatrevisan.wordpress.com
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| | | | | (This is the sixth in a series of posts on online optimization techniques and their ``applications'' to complexity theory, combinatorics and pseudorandomness. The plan for this series of posts is to alternate one post explaining a result from the theory of online convex optimization and one post explaining an ``application.'' The first two posts were... | |
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almostsuremath.com
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| | | | | The Rademacher distribution is probably the simplest nontrivial probability distribution that you can imagine. This is a discrete distribution taking only the two possible values $latex {\{1,-1\}}&fg=000000$, each occurring with equal probability. A random variable X has the Rademacher distribution if $latex \displaystyle {\mathbb P}(X=1)={\mathbb P}(X=-1)=1/2. &fg=000000$ A Randemacher sequence is an IID sequence of... | |
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jaywillmath.wordpress.com
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| | | | | In the previous post, I discussed a technique due to Neumann and Neumann for embedding any countable group into a 2-generated group, and mentioned in passing that they used the same ideas to create a finitely generated 3-solvable non-Hopfian group. This construction turned out to be very useful to my own research, but to describe... | |
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sriku.org
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| | | [AI summary] The article explains how to generate random numbers that follow a specific probability distribution using a uniform random number generator, focusing on methods involving inverse transform sampling and handling both continuous and discrete cases. | ||
