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Q-valued neural network as a system of fast identification and pattern recognition, , , and . (December 2004)Transformation of Categorical Features into Real Using Low-Rank Approximations.. RuSSIR, volume 505 of Communications in Computer and Information Science, page 253-262. Springer, (2014)Derived categories of curves as components of Fano manifolds., and . J. Lond. Math. Soc., 97 (1): 24-46 (2018)Application of Potts-Model Perceptron for Binary Patterns Identification., , and . ICANN (1), volume 5163 of Lecture Notes in Computer Science, page 553-561. Springer, (2008)Vector Perceptron Learning Algorithm Using Linear Programming., , and . ICANN (2), volume 7553 of Lecture Notes in Computer Science, page 197-204. Springer, (2012)On the Probability of Finding Local Minima in Optimization Problems., , and . IJCNN, page 3243-3248. IEEE, (2006)Operator formalism for optical neural network based on the parametrical four-wave mixing process, , and . CoRR, (2012)An Effective Associative Memory for Pattern Recognition., , and . IDA, volume 2810 of Lecture Notes in Computer Science, page 179-186. Springer, (2003)Estimation of Performance of the Hopfield Randomized Memory., , and . Probl. Inf. Transm., 37 (2): 155-164 (2001)Q-valued neural network as a system of fast identification and pattern recognition, , , and . CoRR, (2004)