Abstract
We show that the pre-processing versions of the closest vector problem and the nearest codeword problem are \({\mathsf {NP}}\) -hard to approximate within any constant factor.
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Dorit Aharonov & Oded Regev (2005). Lattice problems in NP \({\cap}\) co-NP. J. ACM 52, 749–765. ISSN 0004-5411. URL http://doi.acm.org/10.1145/1089023.1089025.
M. Ajtai (1996). Generating hard instances of lattice problems. In Proceedings of the ACM Symposium on the Theory of Computing, number 28, 99–108.
Mikhail Alekhnovich, Subhash Khot, Guy Kindler & Nisheeth K. Vishnoi (2005). Hardness of Approximating the Closest Vector Problem with Pre-Processing. In Proceedings of the 46nd Annual IEEE Symposium on Foundations of Computer Science, Pittsburgh PA, 216–225.
Bruck J., Naor M. (1990) The hardness of decoding linear codes with preprocessing. IEEE Transactions on Information Theory 36(2): 381–385
Irit Dinur, Venkatesan Guruswami, Subhash Khot, Oded Regev (2005) A New Multilayered PCP and the Hardness of Hypergraph Vertex Cover. SIAM J. Comput. 34(5): 1129–1146
Irit Dinur, Guy Kindler, Ran Raz, Shmuel Safra (2003) Approximating CVP to Within Almost-Polynomial Factors is NP-Hard. Combinatorica 23(2): 205–243
Feige U., Micciancio D. (2004) The inapproximability of lattice and coding problems with preprocessing. Journal of Computer and System Sciences 69(1): 45–67
R. Kannan (1983). Improved algorithms for integer programming and related lattice problems. In Proceedings of the ACM Symposium on the Theory of Computing, number 15, 193–206.
Lagarias J.C., Lenstra H.W., Schnorr C.P. (1990) Korkine-Zolotarev bases and successive minima of a lattice and its reciprocal lattice. Combinatorica 10: 333–348
Lagarias J.C., Odlyzko A.M. (1985) Solving low-density subset sum problems. Journal of the ACM 32(1): 229–246
Lenstra A.K., Lenstra H.W., Lovász L. (1982) Factoring polynomials with rational coefficients. Math. Ann. 261: 513–534
H.W. Lenstra (1981). Integer programming with a fixed number of variables. Technical Report 81-03, Univ. of Amsterdam, Amsterdam.
Yi-Kai Liu, Vadim Lyubashevsky & Daniele Micciancio (2006). On Bounded Distance Decoding for General Lattices. In APPROX-RANDOM, 450–461.
Carsten Lund., Mihalis Yannakakis (1994) On the Hardness of Approximating Minimization Problems. J. ACM 41(5): 960–981
Micciancio D. (2001) The Hardness of the Closest Vector Problem with Preprocessing. IEEE Transactions on Information Theory 47: 1212–1215
D. Micciancio & S. Goldwasser (2002). Complexity of lattice problems: A cryptographic perspective, volume 671. Kluwer Academic Publishers.
Daniele Micciancio & Panagiotis Voulgaris (2010). A deterministic single exponential time algorithm for most lattice problems based on voronoi cell computations. In Proceedings of the ACM Symposium on the Theory of Computing, 351–358.
Phong Quang Nguyen (2010). Hermite’s Constant and Lattice Algorithms. In The LLL Algorithm: Survey and Applications, Phong Q. Nguyen & Brigitte Vallée, editors, Information Security and Cryptography Series, 19–69. Springer.
Oded Regev (2004) Improved Inapproximability of Lattice and Coding Problems With Preprocessing. IEEE Transactions on Information Theory 50(9): 2031–2037
Oded Regev & Ricky Rosen (2006). Lattice problems and norm embeddings. In Proceedings of the ACM Symposium on the Theory of Computing, 447–456.
Claus-Peter Schnorr (1987) A Hierarchy of Polynomial Time Lattice Basis Reduction Algorithms. Theor. Comput. Sci. 53: 201–224
Michael Sipser., Daniel A. Spielman (1996) Expander codes. IEEE Transactions on Information Theory 42(6): 1710–1722
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Alekhnovich, M., Khot, S.A., Kindler, G. et al. Hardness of Approximating the Closest Vector Problem with Pre-Processing. comput. complex. 20, 741–753 (2011). https://doi.org/10.1007/s00037-011-0031-3
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DOI: https://doi.org/10.1007/s00037-011-0031-3