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Semantics, Representations and Grammars for Deep Learning
[article]
2015
arXiv
pre-print
Deep learning is currently the subject of intensive study. However, fundamental concepts such as representations are not formally defined -- researchers "know them when they see them" -- and there is no common language for describing and analyzing algorithms. This essay proposes an abstract framework that identifies the essential features of current practice and may provide a foundation for future developments. The backbone of almost all deep learning algorithms is backpropagation, which is
arXiv:1509.08627v1
fatcat:u6tbkcdsafcbhbxlxvyvgtltt4