2
votes
Accepted
Decomposing multidimensional matrices into contraction of 2-dimentional matrices using the singular value decomposition.
The minimal number of summands in your decomposition is called the tensor rank of a hypermatrix $c$ (or the corresponding tensor). Computing tensor rank is NP-hard, and even approximating it up to a ...
- 1,508
1
vote
Distance between two vertices picked at random from random graph.
This depends on your random graph model. Peeyush's answer is true for fixed $p$, however in a random graph model, we often take $p \in \Theta(\frac{1}{n})$, then by the same reasoning, sending $n\to \...
- 11
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