According to not necessarily reliable internet sources, Georg Cantor "told his colleagues and friends that he was proud of his choice of the letter aleph to symbolize the transfinite numbers, since ...

This problem is very roughly analogous to having a square piece of paper and you want to fold it so that it fits into a cube, except both the paper and cube are discrete, and the folds of the paper ...

This paper explains why smooth numbers play a key role in almost every modern integer factorization algorithm. Maybe it lists the exceptions, but I couldn't find them. http://www.math.dartmouth.edu/~...

Maybe relevant: "Lifshitz tails for spectra of Erdős–Rényi random graphs" Oleksiy Khorunzhiy, Werner Kirsch, and Peter Müller "We consider the discrete Laplace operator (the graph Laplacian) on ...

If they are co-authors on the paper then add them alphabetically as is customary for math journals. Otherwise if they are not co-authors then just mention them in acknowledgements. If you want to ...

I call a Strongly Connected Component (SCC) "ergodic" if we cannot get out of it, and "transient" otherwise. It suffices to compute the probability ρ(C) to end up in each ergodic ...

This isn't an answer so please vote it down, but if you want a closed-form approximation then you can say that you begin with some finite distribution of coin amounts, so instead of saying you start ...

I am poking around at a large matrix (with dimension 2^N×2^N). The matrix is made up of ... corresponding to specific interactions is it thus possible to implicitly find Eigenvalues of it, without ...

You can use a Markov chain on the positions. In ten moves you can't get too far, so you can use a finite grid. In your specific example, the probability of ending up at least 4 blocks away is about 0....

If you adjust the diagonal accordingly then yes, because it would correspond to the Laplacian matrix of a slightly different edge-weighted graph.

If X is the continuous normal random variable and you write the discretized random variable Z as X + Y, then Var(Z) = Var(X) + Var(Y) + 2 Cov(X, Y). When sigma is large enough that Y becomes almost ...

This paper explains entropy estimation without distribution estimation in the undersampled regime.

Use whatever random planar graph sampler to get a planar graph with blue vertices. Put a red vertex on each edge.

I am looking for a general case. It seems to be a folk-lore that the skewness of one sided distributions (say positive sided) is positive. I am looking for a formal argument for/against it. This ...