Dilated Recurrent Neural Networks

NeurIPS 2017 Shiyu ChangYang ZhangWei HanMo YuXiaoxiao GuoWei TanXiaodong CuiMichael WitbrockMark Hasegawa-JohnsonThomas S. Huang

Learning with recurrent neural networks (RNNs) on long sequences is a notoriously difficult task. There are three major challenges: 1) complex dependencies, 2) vanishing and exploding gradients, and 3) efficient parallelization... (read more)

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Evaluation results from the paper


Task Dataset Model Metric name Metric value Global rank Compare
Sequential Image Classification Sequential MNIST Dilated GRU Unpermuted Accuracy 99.2% # 1
Sequential Image Classification Sequential MNIST Dilated GRU Permuted Accuracy 94.6% # 4