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Deep web: approaching to cyber irresponsibilityDeep web: aproximaciones a la ciber irresponsabilidadDeep web: abordagens para a irresponsabilidade cibernética
(Universidad Militar Nueva Granada, 2014)
Deep web: approaching to cyber irresponsibilityDeep web: aproximaciones a la ciber irresponsabilidadDeep web: abordagens para a irresponsabilidade cibernética
(Universidad Militar Nueva Granada, 2014)
Fine Tuning Deep Boltzmann Machines Through Meta-Heuristic Approaches
(Ieee, 2018-01-01)
The Deep learning framework has been widely used in different applications from medicine to engineering. However, there is a lack of works that manage to deal with the issue of hyperparameter fine-tuning, since machine ...
Deep Web and Dark Web: similarities and dissiparities in the context of Information Science
(Pontificia Universidade Catolica Campinas, 2020-01-01)
In this article, we aim to demystify the Deep Web and the Dark Web, in addition to presenting the main similarities and disparities between them, essentially in regard to their: (1)Term; (2) Definition; (3) Metaphorical ...
Learning Parameters in Deep Belief Networks Through Firefly Algorithm
(Springer, 2016-01-01)
Restricted Boltzmann Machines (RBMs) are among the most widely pursed techniques in the context of deep learning-based applications. Their usage enables sundry parallel implementations, which have become pivotal in nowadays ...
Temperature-Based Deep Boltzmann Machines
(Springer, 2018-08-01)
Deep learning techniques have been paramount in the last years, mainly due to their outstanding results in a number of applications, that range from speech recognition to face-based user identification. Despite other ...