… TRAINING ALGORITHMS The learning algorithm constitutes the main part of Deep Learning…
The number of layers differentiates the deep neural network from shallow ones. The higher …

… of development, deep learning now is one of the most efficient tools compared to other
machinelearning algorithms with great performance. We have seen a few deep learning methods …

… learning algorithms, which aim at discovering multiple levels of distributed representations.
Recently, numerous deep learning algorithms … -art in deep learning algorithms in computer …

… Conventional deep learning algorithms, especially the deep convolutional networks (ConvNets)
have achieved many success state-of-art results. However, directly applying ConvNets …

… With the advent of big data era, deep learning (… algorithms are characterized with powerful
feature learning and expression capabilities compared with the traditional machine learning (…

… for neuroscience to offer much guidance for the learning algorithms we use to train these
architectures. Media accounts often emphasize the similarity of deep learning to the brain. …

… learning techniques has been proposed for the automated detection of diabetes in a non-invasive
way. Deep learning techniques, which can self-learn … signals employing deep learning …

… imaging applications using these algorithms to diagnose the … deep learning algorithms
are important ways in medical imaging to predict the symptoms of early disease. Deep learning …

… We think that deep learning will have many more successes in the near future because it
requires very … New learning algorithms and architectures that are currently being developed for …

… The rapid development of cybersecurity attack detection based on deep learning algorithms
is summarized in this paper. The applications of deep learning in cybersecurity attacks are …