Matches in DBpedia 2014 for { <http://dbpedia.org/resource/Learning_with_errors> ?p ?o. }
Showing items 1 to 13 of
13
with 100 items per page.
- Learning_with_errors abstract "Learning with errors (LWE) is a problem in machine learning that is conjectured to be hard to solve. It is a generalization of the parity learning problem, introduced by Oded Regev in 2005. Regev showed, furthermore, that the LWE problem is as hard to solve as several worst-case lattice problems. The LWE problem has recently been used as a hardness assumption to create public-key cryptosystems.An algorithm is said to solve the LWE problem if, when given access to samples where and , with the assurance, for some fixed linear function that with high probability and deviates from it according to some known noise model, the algorithm can recreate or some close approximation of it with high probability.".
- Learning_with_errors wikiPageID "23864530".
- Learning_with_errors wikiPageRevisionID "574543928".
- Learning_with_errors hasPhotoCollection Learning_with_errors.
- Learning_with_errors subject Category:Cryptography.
- Learning_with_errors subject Category:Machine_learning.
- Learning_with_errors comment "Learning with errors (LWE) is a problem in machine learning that is conjectured to be hard to solve. It is a generalization of the parity learning problem, introduced by Oded Regev in 2005. Regev showed, furthermore, that the LWE problem is as hard to solve as several worst-case lattice problems.".
- Learning_with_errors label "Learning with errors".
- Learning_with_errors sameAs m.076yjmm.
- Learning_with_errors sameAs Q6510239.
- Learning_with_errors sameAs Q6510239.
- Learning_with_errors wasDerivedFrom Learning_with_errors?oldid=574543928.
- Learning_with_errors isPrimaryTopicOf Learning_with_errors.