Approximating the SVP to within a Factor is NP-Hard under Randomized Reductions
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[1] Jacques Stern,et al. The hardness of approximate optima in lattices, codes, and systems of linear equations , 1993, Proceedings of 1993 IEEE 34th Annual Foundations of Computer Science.
[2] Jin-Yi Cai,et al. An improved worst-case to average-case connection for lattice problems , 1997, Proceedings 38th Annual Symposium on Foundations of Computer Science.
[3] Jörg M. Wills,et al. Handbook of Convex Geometry , 1993 .
[4] L. Lovász,et al. Geometric Algorithms and Combinatorial Optimization , 1981 .
[5] Miklós Ajtai,et al. The shortest vector problem in L2 is NP-hard for randomized reductions (extended abstract) , 1998, STOC '98.
[6] Oded Goldreich,et al. Public-Key Cryptosystems from Lattice Reduction Problems , 1996, CRYPTO.
[7] Miklós Ajtai,et al. Generating Hard Instances of Lattice Problems , 1996, Electron. Colloquium Comput. Complex..
[8] Jeffrey C. Lagarias. The computational complexity of simultaneous Diophantine approximation problems , 1982, FOCS 1982.
[9] Oded Goldreich,et al. On the limits of non-approximability of lattice problems , 1998, STOC '98.
[10] Cynthia Dwork,et al. A public-key cryptosystem with worst-case/average-case equivalence , 1997, STOC '97.
[11] László Lovász,et al. Algorithmic theory of numbers, graphs and convexity , 1986, CBMS-NSF regional conference series in applied mathematics.