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Meta-learning [1] [2] is a subfield of machine learning where automatic learning algorithms are applied to metadata about machine learning experiments. As of 2017, the term had not found a standard interpretation, however the main goal is to use such metadata to understand how automatic learning can become flexible in solving learning problems, hence to improve the performance of existing ...
Microsoft SEAL comes with two different homomorphic encryption schemes with very different properties: BFV : [ 5 ] The BFV scheme allows modular arithmetic to be performed on encrypted integers. For applications where exact values are necessary, the BFV scheme is the only choice.
Encryption, by itself, can protect the confidentiality of messages, but other techniques are still needed to protect the integrity and authenticity of a message; for example, verification of a message authentication code (MAC) or a digital signature usually done by a hashing algorithm or a PGP signature.
One example of a public-key protocol is given by Khalil Shihab. He describes the decryption scheme and the public key creation that are based on a backpropagation neural network. The encryption scheme and the private key creation process are based on Boolean algebra. This technique has the advantage of small time and memory complexities.
In 1996, Miklós Ajtai introduced the first lattice-based cryptographic construction whose security could be based on the hardness of well-studied lattice problems, [3] and Cynthia Dwork showed that a certain average-case lattice problem, known as short integer solutions (SIS), is at least as hard to solve as a worst-case lattice problem. [4]
Alice selects a binary (n, k)-linear Goppa code, G, capable of correcting t errors. This code possesses an efficient decoding algorithm. Alice generates a (n − k) × n parity check matrix, H, for the code, G. Alice selects a random (n − k) × (n − k) binary non-singular matrix, S. Alice selects a random n × n permutation matrix, P.
Hidden Field Equations has four basic variations namely +,-,v and f and it is possible to combine them in various way. The basic principle is the following: 01. The + sign consists of linearity mixing of the public equations with some random equations. 02. The -sign is due to Adi Shamir and intends to remove the redundancy 'r' of the public ...
In cryptography, learning with errors (LWE) is a mathematical problem that is widely used to create secure encryption algorithms. [1] It is based on the idea of representing secret information as a set of equations with errors. In other words, LWE is a way to hide the value of a secret by introducing noise to it. [2]