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Crafting Adversarial Examples for Neural Machine Translation
We first show the current NMT adversarial attacks may be improperly estimated by the commonly used mono-directional translation, and we propose to leverage the round-trip translation technique to build valid metrics for evaluating NMT adversarial attacks.
Error-feedback stochastic modeling strategy for time series forecasting with convolutional neural networks
Despite the superiority of convolutional neural networks demonstrated in time series modeling and forecasting, it has not been fully explored on the design of the neural network architecture and the tuning of the hyper-parameters.
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