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A SOM-based Gradient-Free Deep Learning Method with Convergence Analysis. (arXiv:2101.05612v2 [cs.LG] UPDATED)
Jan. 27, 2022, 2:11 a.m. | Shaosheng Xu, Jinde Cao, Yichao Cao, Tong Wang
cs.LG updates on arXiv.org arxiv.org
As gradient descent method in deep learning causes a series of questions,
this paper proposes a novel gradient-free deep learning structure. By adding a
new module into traditional Self-Organizing Map and introducing residual into
the map, a Deep Valued Self-Organizing Map network is constructed. And analysis
about the convergence performance of such a deep Valued Self-Organizing Map
network is proved in this paper, which gives an inequality about the designed
parameters with the dimension of inputs and the loss of …
More from arxiv.org / cs.LG updates on arXiv.org
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