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An alternative approach to train neural networks using monotone variational inequality. (arXiv:2202.08876v3 [stat.ML] UPDATED)
Aug. 11, 2022, 1:10 a.m. | Chen Xu, Xiuyuan Cheng, Yao Xie
cs.LG updates on arXiv.org arxiv.org
Despite the vast empirical success of neural networks, theoretical
understanding of the training procedures remains limited, especially in
providing performance guarantees of testing performance due to the non-convex
nature of the optimization problem. The current paper investigates an
alternative approach of neural network training by reducing to another problem
with convex structure -- to solve a monotone variational inequality (MVI) --
inspired by a recent work of (Juditsky & Nemirovsky, 2019). The solution to MVI
can be found by computationally …
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