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A sequential regularized piecewise affine algorithm for nonconvex nonsmooth multicomposite optimization in RNN training
This paper focuses on a class of nonconvex nonsmooth multicomposite optimization problems for training RNNs (Recurrent Neural Networks). We first establish easily verifiable conditions under which an approximate first-order d-stationary point of the problem is guaranteed to be an approximate second-
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