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Ring Learning with Errors Cryptography
2020In this chapter, we will discuss Ring-Learning with Errors cryptography (RLWE) as one of the most powerful and challenging approaches for developing professional and complex applications and systems.
Marius Iulian Mihailescu +1 more
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New Electronics, 2023
Large-language models threaten to upend software and hardware development as we know it, but can they really deliver the goods? CHRIS EDWARDS investigates
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Large-language models threaten to upend software and hardware development as we know it, but can they really deliver the goods? CHRIS EDWARDS investigates
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Proceedings of the 55th Annual Design Automation Conference, 2018
The Learning with Errors (LWE) problem is a novel foundation of a variety of cryptographic applications, including quantumly-secure public-key encryption, digital signature, and fully homomorphic encryption. In this work, we propose an approximate decryption technique for LWE-based cryptosystems.
Song Bian +2 more
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The Learning with Errors (LWE) problem is a novel foundation of a variety of cryptographic applications, including quantumly-secure public-key encryption, digital signature, and fully homomorphic encryption. In this work, we propose an approximate decryption technique for LWE-based cryptosystems.
Song Bian +2 more
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Feedback Error Learning with insufficient excitation
2008 47th IEEE Conference on Decision and Control, 2008Control-theoretical studies on feedback error learning (FEL) have been active recently. The authors generalized this scheme to multi-input multi-output (MIMO) systems with application to writing one-stroke characters by a two-link manipulator.
B. ALALI, K. HIRATA, K. SUGIMOTO
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Efficient Laconic Cryptography from Learning with Errors
2023Laconic cryptography is an emerging paradigm that enables cryptographic primitives with sublinear communication complexity in just two messages. In particular, a two-message protocol between Alice and Bob is called laconic if its communication and computation complexity are essentially independent of the size of Alice's input.
Dottling N. +5 more
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Communications with Learning Errors
2018In the real-life scenario of human communications, both the local communication process of agents and the information propagation on the underlying network affect the achievement and speed of global convergence. For example, if agents can learn fast and correctly from local communications, and thereafter teach their neighbors to effectively learn the ...
Guanrong Chen, Yang Lou
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Feedback Error Learning with basis function networks
2006 IEEE Conference on Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control, 2006In this paper, we examine the stability properties of Feedback Error Learning, a model for biological control systems. We consider a specific model for cerebellar learning during fast voluntary movements. We assume that the feedforward approximation is represented by a basis function network.
Abraham Ishihara +2 more
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Middle-Product Learning with Errors
2017We introduce a new variant \(\mathsf {MP}\text {-}\mathsf {LWE}\) of the Learning With Errors problem (\(\mathsf {LWE}\)) making use of the Middle Product between polynomials modulo an integer q. We exhibit a reduction from the Polynomial-\(\mathsf {LWE}\) problem (\(\mathsf {PLWE}\)) parametrized by a polynomial f, to \(\mathsf {MP}\text {-}\mathsf ...
Steinfeld, Ron +3 more
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