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The increasing complexity of deep neural networks (DNNs) has made it challenging to exploit existing large-scale data processing pipelines for handling massive data and parameters involved in DNN training.
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Petuum: A new platform for distributed machine learning on big data
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Investigating nmf speech enhancement for neural network based acoustic models
J. T. Geiger, et al · 2014
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Caffe: Convolutional architecture for fast feature embedding
Y. Jia, et al · 2014
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Deep residual learning for image recognition
K. He, et al · 2015
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J. K. Chorowski, et al · 2015
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TensorFlow: Large-scale machine learning on heterogeneous systems, 2015
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ImageNet Large Scale Visual Recognition Challenge
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