Reduction from k-Clique to CFG Recognition: Difference between revisions
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== Implications == | == Implications == | ||
assume: k-Clique Hypothesis<br/>then: there is no $O(N^{\ | assume: k-Clique Hypothesis<br/>then: there is no $O(N^{\omega-\epsilon}) time algorithm for target for any $\epsilon > {0}$ | ||
== Year == | == Year == | ||
Revision as of 09:47, 28 April 2023
FROM: k-Clique TO: CFG Recognition
Description
Implications
assume: k-Clique Hypothesis
then: there is no $O(N^{\omega-\epsilon}) time algorithm for target for any $\epsilon > {0}$
Year
2017
Reference
Abboud, A., Backurs, A., Bringmann, K., & Künnemann, M. (2017, October). Fine-grained complexity of analyzing compressed data: Quantifying improvements over decompress-and-solve. In 2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS) (pp. 192-203). IEEE.
https://ieeexplore-ieee-org.ezproxy.canberra.edu.au/abstract/document/8104058