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pro vyhledávání: '"Qu, Cheng Kevin"'
Deep neural networks (DNNs) have been successfully applied to many real-world problems, but a complete understanding of their dynamical and computational principles is still lacking. Conventional theoretical frameworks for analysing DNNs often assume
Externí odkaz:
http://arxiv.org/abs/2203.12967
Learning in deep neural networks (DNNs) is implemented through minimizing a highly non-convex loss function, typically by a stochastic gradient descent (SGD) method. This learning process can effectively find good wide minima without being trapped in
Externí odkaz:
http://arxiv.org/abs/2009.10588
Publikováno v:
In Neural Networks May 2022 149:18-28
