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The video is misleading when it spreads the idea that "polynomial time" equals "practical," or "fast". It's nice and simple to talk like that, but I don't thi
by swehner 11y ago
The video is misleading when it spreads the idea that "polynomial time" equals "practical," or "fast".
It's nice and simple to talk like that, but I don't think it's particularly useful or helpful.
For example, there is a linear time algorithm for deciding whether two planar graphs are isomorphic (Hopcroft,Wong 1974). But the constant of the asymptotic time bound of their algorithm so large that it was not useful or practical (see end of abstract, http://dl.acm.org/citation.cfm?id=803896 http://dl.acm.org/citation.cfm?id=803896)
Only in 2004 did Kukluk, Holder, Cook publish a quadratic time algorithm, "suitable for practical implementation." http://www.eecs.wsu.edu/~holder/pubs/KuklukJGAA04.pdf http://www.eecs.wsu.edu/~holder/pubs/KuklukJGAA04.pdf
More such examples are listed at "Polynomial-time algorithms with huge exponent/constant," http://cstheory.stackexchange.com/questions/6660/polynomial-time-algorithms-with-huge-exponent-constant http://cstheory.stackexchange.com/questions/6660/polynomial-...
- peeters 11y agoI think the video addresses it in a fair and approachable manner. It makes it clear that the value is in scaling algorithms to larger inputs, and even shows so in a graph. When dealing with unbounded scaling, the constants typically do not matter.