Accelerating Deep Neural Network Training with Inconsistent Stochastic
Gradient Descent

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Accelerating Deep Neural Network Training with Inconsistent Stochastic Gradient Descent

17 March 2016

Martin Renqiang Min

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Papers citing "Accelerating Deep Neural Network Training with Inconsistent Stochastic Gradient Descent"

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Title
Batch-FPM: Random batch-update multi-parameter physical Fourier ptychography neural networkIEEE Transactions on Computational Imaging (TCI), 2024 Ruiqing Sun Delong Yang Yiyan Su Shaohui Zhang Qun Hao 88 2 0 25 Aug 2024
Multiple Importance Sampling for Stochastic Gradient Estimation Corentin Salaün Xingchang Huang Iliyan Georgiev Niloy J. Mitra Gurprit Singh 217 2 0 22 Jul 2024
Importance Sampling for Stochastic Gradient Descent in Deep Neural Networks Thibault Lahire 112 3 0 29 Mar 2023
PA&DA: Jointly Sampling PAth and DAta for Consistent NASComputer Vision and Pattern Recognition (CVPR), 2023 Shunong Lu Yu Hu Longxing Yang Zihao Sun Jilin Mei Jianchao Tan Chengru Song 149 13 0 28 Feb 2023
Large Batch Experience Replay Thibault Lahire Matthieu Geist Emmanuel Rachelson OffRL 229 16 0 04 Oct 2021
Block-term Tensor Neural NetworksNeural Networks (NN), 2020 Jinmian Ye Guangxi Li Di Chen Haiqin Yang Shandian Zhe Zenglin Xu 237 34 0 10 Oct 2020
Neural Network Retraining for Model Serving Diego Klabjan Xiaofeng Zhu CLL 197 11 0 29 Apr 2020
Dynamic Stale Synchronous Parallel Distributed Training for Deep LearningIEEE International Conference on Distributed Computing Systems (ICDCS), 2019 Xing Zhao Aijun An Junfeng Liu Bin Chen 151 66 0 16 Aug 2019
Dual-branch residual network for lung nodule segmentationApplied Soft Computing (Appl Soft Comput), 2019 Haichao Cao Hong Liu E. Song C. Hung Guangzhi Ma Xiangyang Xu Renchao Jin Jianguo Lu 105 123 0 21 May 2019
SuperNeurons: FFT-based Gradient Sparsification in the Distributed Training of Deep Neural Networks Linnan Wang Wei Wu Junyu Zhang Hang Liu G. Bosilca Maurice Herlihy Rodrigo Fonseca GNN 91 5 0 21 Nov 2018
Compositional Stochastic Average Gradient for Machine Learning and Related Applications Tsung-Yu Hsieh Y. El-Manzalawy Yiwei Sun Vasant Honavar 141 1 0 04 Sep 2018
Not All Samples Are Created Equal: Deep Learning with Importance SamplingInternational Conference on Machine Learning (ICML), 2018 Angelos Katharopoulos François Fleuret 322 596 0 02 Mar 2018
SuperNeurons: Dynamic GPU Memory Management for Training Deep Neural Networks Linnan Wang Jinmian Ye Yiyang Zhao Wei Wu Ang Li Shuaiwen Leon Song Zenglin Xu Tim Kraska 3DH 184 286 0 13 Jan 2018
A multi-candidate electronic voting scheme with unlimited participants Xi Zhao Yong Ding Quanyu Zhao 51 1 0 29 Dec 2017
Learning Compact Recurrent Neural Networks with Block-Term Tensor Decomposition Jinmian Ye Linnan Wang Guangxi Li Di Chen Shandian Zhe Xinqi Chu Zenglin Xu 220 140 0 14 Dec 2017
Biased Importance Sampling for Deep Neural Network Training Angelos Katharopoulos François Fleuret 197 74 0 31 May 2017
Efficient Communications in Training Large Scale Neural Networks Linnan Wang Wei Wu G. Bosilca R. Vuduc Zenglin Xu 154 18 0 14 Nov 2016
BLASX: A High Performance Level-3 BLAS Library for Heterogeneous Multi-GPU Computing Linnan Wang Wei Wu Jianxiong Xiao Yezhou Yang 104 54 0 16 Oct 2015