Results 251 to 260 of about 6,745,331 (273)
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2002
In Chapter 2 we described algorithms to (approximately) solve SVP and CVP. These algorithms exhibit relatively good performance as far as the running time is concerned. In particular, they terminate within a time bound that is polynomial in the size of the input.
Daniele Micciancio, Shafi Goldwasser
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In Chapter 2 we described algorithms to (approximately) solve SVP and CVP. These algorithms exhibit relatively good performance as far as the running time is concerned. In particular, they terminate within a time bound that is polynomial in the size of the input.
Daniele Micciancio, Shafi Goldwasser
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Sampling short lattice vectors and the closest lattice vector problem
Proceedings 17th IEEE Annual Conference on Computational Complexity, 2003We present a 2/sup O(n)/ time Turing reduction from the closest lattice vector problem to the shortest lattice vector problem. Our reduction assumes access to a subroutine that solves SVP exactly and a subroutine to sample short vectors from a lattice, and computes a (1+/spl epsi/)-approximation to CVP As a consequence, using the SVP algorithm from ...
Miklós Ajtai +2 more
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Complexity of the Closest Vector Problem in a Lattice Generated by (0,1)-Matrix
Information Processing Letters, 1992The paper establishes complexity of the well-known closest vector problem in an arbitrary norm in a lattice generated by a (0,1)-matrix --- the authors refer to this problem as (0,1)-CVP. In finite norms, this problem is NP-hard when the input vector contains nonzero elements.
Boleslaw Szymanski, Balaram Sinharoy
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The Hardness of the Closest Vector Problem With Preprocessing Over$ell_infty$Norm
IEEE Transactions on Information Theory, 2006We show that the closest vector problem with preprocessing (CVPP) over lscr infin norm (CVPPinfin) is NP-hard. The result is obtained by the reduction from the subset sum problem with preprocessing to CVPPinfin. The reduction also shows the NP-hardness of CVPinfin, which is much simpler than all previously known proofs.
W. Chen, J. Meng
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Distance-Preserving Vector Space Embedding for the Closest String Problem
2016 23rd International Conference on Pattern Recognition (ICPR), 2016The closest string problem is a core problem in computational biology with applications in other fields like coding theory. Many algorithms exist to solve this problem, but due to its inherent high computational complexity (typically NP-hard), it can only be solved efficiently by restricting the search space to a specific range of parameters.
Xiaoyi Jiang, Andreas Nienkotter
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Approximating Closest Vector Problem in $$\ell _\infty $$ Norm Revisited
2019The security of most lattice-based cryptography schemes are based on two computational hard problems which are the Short Integer Solution (SIS) and Learning With Errors (LWE) problems. The computational complexity of SIS and LWE problems are related to approximating Shortest Vector Problem (SVP) and Bounded Distance Decoding Problem (BDD ...
Wenbin Chen, Jianer Chen
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Corrigenda: Complexity of the closest vector problem in a lattice generated by (0,1)-matrix
Inf. Process. Lett., 1992zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Boleslaw K. Szymanski, Balaram Sinharoy
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Almost Polynomial Factor Hardness for Closest Vector Problem With Preprocessing
SIAM Journal on Computing, 2014Nisheeth K. Vishnoi
exaly
Closest Vector Problem-Based Proof of Work Mechanism for Post-Quantum Blockchain
Lecture Notes in Networks and Systems, 2022exaly