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Hardness of Approximating the Shortest Vector Problem in High Lp Norms
Cambridge, Massachusettes October 11-October 14
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/SFCS.2003.123820344th Annual IEEE Symposium on Foundat ...
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Subhash Khot, Princeton University
We show that for every \varepsilon > 0, there is a constant p(\varepsilon) such that for all integers p \geqslant p(\varepsilon), it is NP-hard to approximate the Shortest Vector Problem in Lp norm within factor p^{1 - \varepsilon } under randomized reductions. For large values of p, this improves the factor 2^{{1 \mathord{\left/ {\vphantom {1 p}} \right. \kern-\nulldelimiterspace} p}} - \delta hardness shown by Micciancio.
Citation:
Subhash Khot, "Hardness of Approximating the Shortest Vector Problem in High Lp Norms," focs, pp.290, 44th Annual IEEE Symposium on Foundations of Computer Science (FOCS'03), 2003
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