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Informational capacity and recall quality in sparsely encoded Hopfield-like neural network: analytical approaches and computer simulation ... information is transformed into valuable information with neural net. The individual element of the neural network, i.e., the living neuronal cell, is ... We do so by performing experiments on artificial neural networks in the context of fairness in machine learning, where the goal is to induce fairness in the ... ... neural networks contribute to familiar face recognition. Original language, English. Article number, 117896. Pages (from-to), 1-15. Number of pages, 15. Journal ... The Informational Complexity of Learning: Perspectives on Neural Networks and Generative Grammar is a very interdisciplinary work. Anyone interested in the ... Sep 11, 2020 ... Alternatively, it is. 10. Page 29. 2.1. Preliminaries on convolutional neural networks often found that adding depth to the network by stacking ... ... Learning Capability of Deep Neural Networks: A Positivist Perspective Jaebong Son and Chang Heon Lee. PDF · The Sky Is the Limit: A Review of Drone Research ... Sep 5, 2024 ... In this paper we develop a novel mathematical formalism for the modeling of neural information networks endowed with additional structure in ... classification via convolutional deep neural network. In Proceedings of COLING. 2014, the 25th International Conference on Computational Linguistics ... Dec 20, 2024 ... In ecosystems, financial markets, and neural networks, entropy fluctuates as new information reshapes the probability landscape. 4.2 The ...