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Low-Rank Matrix Approximation with Weights or Missing Data is NP-hard
low-rank matrix approximation weighted low-rank approximation missing data
2011/1/17
Weighted low-rank approximation (WLRA), a dimensionality reduction technique for data anal-
ysis, has been successfully used in several applications, such as in collaborative filtering to design reco...
Unique Shortest Vector Problem for max norm is NP-hard
unique closest vector problem unique subspace avoiding problem Lattice
2009/6/8
The unique Shortest vector problem (uSVP) in lattice theory plays a crucial role in many
public-key cryptosystems. The security of those cryptosystems bases on the hardness of uSVP. However,
so far ...
Knapsack cryptosystems built on NP-hard instances
Knapsack cryptosystems NP-hard instances Probabilistic polynomial reductions
2009/6/3
We construct three public key knapsack cryptosystems. Standard knapsack cryptosystems hide easy
instances of the knapsack problem and have been broken. The systems considered in the article face
thi...