We demonstrate that any logical problem can be solved by Bayesian inference. In this approach, the distinction between complexity classes vanishes. The method is illustrated by solving the 3-SAT problem in polynomial time. Beyond this, Bayesian inference could be the background of artificial neural network theory.
arXiv comments
This version V5: Editorial revisions. 11 pages, no figure. (Initial title:From classical versus quantum algorithms to P versus NP). Additional comments on relations with quantum computing in arXiv: 1312.7551
Linked by 2 identifiable commenters in 2 comments across 1 thread, from Dec 2012 to Dec 2012. Found in 1 HN submission from Mar 2016 to Mar 2016. Open submission discussions.
When I opened this page, I was going to be the third comment, then I got caught up trying to explain why their linked paper [1] (proving P=NP) is non-sense. Unfourtuantly, my habit of assuming that my not understanding something just means that I need to re-read it or play with…
You might as well start with his proof of P=NP http://arxiv.org/pdf/1205.6658.pdf
bzaxView on HNParent context
When I opened this page, I was going to be the third comment, then I got caught up trying to explain why their linked paper [1] (proving P=NP) is non-sense. Unfourtuantly, my habit of assuming that my not understanding something just means that I need to re-read it or play with…
gizmo686View on HNParent context