Sampling Methods for Shortest Vectors, Closest Vectors and Successive Minima-Reference-Cited by-同舟云学术

Sampling Methods for Shortest Vectors, Closest Vectors and Successive Minima

Published: Issue: Volume: Page:65-77
ISSN:0302-9743
Container-title:Automata, Languages and Programming
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Author:

Blömer Johannes,Naewe Stefanie

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-540-73420-8_8.pdf

Reference17 articles.

1. Ajtai, M.: The shortest vector problem in l 2 is NP-hard for randomized reductions. In: Proceedings of the 30th ACM Symposium on Theory of Computing, pp. 10–19. ACM Press, New York (1998)

2. Ajtai, M., Kumar, R., Sivakumar, D.: A sieve algorithm for the shortest lattice vector problem. In: Proceedings of the 33th ACM Symposium on Theory of Computing, pp. 601–610. ACM Press, New York (2001)

3. Ajtai, M., Kumar, R., Sivakumar, D.: Sampling short lattice vectors and the closest lattice vector problem. In: Proceedings of the 17th IEEE Annual Conference on Computational Complexity - CCC, pp. 53–57. IEEE Computer Society Press, Los Alamitos (2002)

4. Babai, L.: On Lovász’ lattice reduction and the nearest lattice point problem. Combinatorica 6(1), 1–13 (1986)

5. Lecture Notes in Computer Science;J. Blömer,2000

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