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Deep learning systems as complex networks
[article]
2018
arXiv
pre-print
Thanks to the availability of large scale digital datasets and massive amounts of computational power, deep learning algorithms can learn representations of data by exploiting multiple levels of abstraction. These machine learning methods have greatly improved the state-of-the-art in many challenging cognitive tasks, such as visual object recognition, speech processing, natural language understanding and automatic translation. In particular, one class of deep learning models, known as deep
arXiv:1809.10941v1
fatcat:qxeiq4qehbawbe3gpdfaujylrm