Exploring Hyper-Parameter Optimization for Neural Machine Translation on GPU Architectures

5 May 2018Robert LimKenneth HeafieldHieu HoangMark BriersAllen Malony

Neural machine translation (NMT) has been accelerated by deep learning neural networks over statistical-based approaches, due to the plethora and programmability of commodity heterogeneous computing architectures such as FPGAs and GPUs and the massive amount of training corpuses generated from news outlets, government agencies and social media. Training a learning classifier for neural networks entails tuning hyper-parameters that would yield the best performance... (read more)

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