On the Complexity of the LWR-Solving BKW Algorithm

The Blum-Kalai-Wasserman algorithm (BKW) is an algorithm for solving the learning parity with noise problem, which was then adapted for solving the learning with errors problem (LWE) by Albrecht et al. Duc et al. applied BKW also to the learning with rounding problem (LWR). The number of blocks is a...

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Veröffentlicht in:	IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences Communications and Computer Sciences, 2020/01/01, Vol.E103.A(1), pp.173-182
Hauptverfasser:	OKADA, Hiroki, TAKAYASU, Atsushi, FUKUSHIMA, Kazuhide, KIYOMOTO, Shinsaku, TAKAGI, Tsuyoshi
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Asymptotic properties Blum-Kalai-Wasserman algorithm Complexity lattice learning with errors learning with rounding Machine learning Optimization Parameters Rounding
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