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nickhar.wordpress.com | ||
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mkatkov.wordpress.com
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| | | | | For probability space $latex (\Omega, \mathcal{F}, \mathbb{P})$ with $latex A \in \mathcal{F}$ the indicator random variable $latex {\bf 1}_A : \Omega \rightarrow \mathbb{R} = \left\{ \begin{array}{cc} 1, & \omega \in A \\ 0, & \omega \notin A \end{array} \right.$ Than expected value of the indicator variable is the probability of the event $latex \omega \in... | |
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lucatrevisan.wordpress.com
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| | | | | Today we will see how to use the analysis of the multiplicative weights algorithm in order to construct pseudorandom sets. The method will yield constructions that are optimal in terms of the size of the pseudorandom set, but not very efficient, although there is at least one case (getting an ``almost pairwise independent'' pseudorandom generator)... | |
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algorithmsoup.wordpress.com
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| | | | | In this post, I want to tell you about what I think might be the world's simplest interesting algorithm. The vertex cover problem. Given a graph $latex {G = (V, E)}&fg=000000$, we want to find the smallest set of vertices $latex {S \subseteq V}&fg=000000$ such that every edge $latex {e \in E}&fg=000000$ is covered by... | |
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craftofcoding.wordpress.com
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| | | Visit the post for more. | ||
