期刊名称：Electronic Colloquium on Computational Complexity
印刷版ISSN：1433-8092
出版年度：1997
卷号：1997
出版社：Universität Trier, Lehrstuhl für Theoretische Computer-Forschung
摘要：Recently Ajtai showed that
to approximate the shortest lattice vector in the $l_2$-norm within a
factor $(1+2^{-\mbox{\tiny dim}^k})$, for a sufficiently large
constant $k$, is NP-hard under randomized reductions.
We improve this result to show that
to approximate a shortest lattice vector within a
factor $(1+ \mbox{dim}^{-\epsilon})$, for any
$\epsilon>0$, is NP-hard under randomized reductions.
Our proof also works for arbitrary $l_p$-norms, $1 \leq p < \infty$.
关键词：Approximation, lattices, NP-hardness, shortest vector problem
