883 citations · 1.1k across the 30 of their papers we have counts for
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PSO-PS: Parameter Synchronization with Particle Swarm Optimization for Distributed Training of Deep Neural Networks
Qing Ye, Yuxuan Han, Yanan sun +1
Parameter updating is an important stage in parallelism-based distributed deep learning. Synchronous methods are widely used in distributed training the Deep Neural Networks (DNNs)…
HPSGD: Hierarchical Parallel SGD With Stale Gradients Featuring
Yuhao Zhou, Qing Ye, Hailun Zhang +1
While distributed training significantly speeds up the training process of the deep neural network (DNN), the utilization of the cluster is relatively low due to the time-consuming…
DBS: Dynamic Batch Size For Distributed Deep Neural Network Training
Qing Ye, Yuhao Zhou, Mingjia Shi +2
Synchronous strategies with data parallelism, such as the Synchronous StochasticGradient Descent (S-SGD) and the model averaging methods, are widely utilizedin distributed training…
Learning Inverse Mapping by Autoencoder based Generative Adversarial Nets
Junyu Luo, Yong Xu, Chenwei Tang +1
The inverse mapping of GANs'(Generative Adversarial Nets) generator has a great potential value.Hence, some works have been developed to construct the inverse function of generator…