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Lecture Notes in Computer Science
The "learning with errors" (LWE) problem is to distinguish random linear equations, which have been perturbed by a small amount of noise, from truly uniform ones. The problem has been shown to be as hard as worst-case lattice problems, and in recent years it has served as the foundation for a plethora of cryptographic applications. Unfortunately, these applications are rather inefficient due to an inherent quadratic overhead in the use of LWE. A main open question was whether LWE and itsdoi:10.1007/978-3-642-13190-5_1 fatcat:htckcqetq5ehhkqjjrw4xmaqui