An Efficient, Distributed Stochastic Gradient Descent Algorithm for Deep-Learning Applications

Author:

Cong Guojing,Bhardwaj Onkar,Feng Minwei

Publisher

IEEE

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Shuffling-type gradient method with bandwidth-based step sizes for finite-sum optimization;Neural Networks;2024-11

2. Tree Network Design for Faster Distributed Machine Learning Process with Distributed Dual Coordinate Ascent;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

3. Enhancing Blast Design Efficiency for Rock Fragmentation with Gradient Descent and Artificial Neural Networks: An Optimization Study;2023 4th International Conference on Computers and Artificial Intelligence Technology (CAIT);2023-12-13

4. Distributed Dual Coordinate Ascent With Imbalanced Data on a General Tree Network;2023 IEEE 33rd International Workshop on Machine Learning for Signal Processing (MLSP);2023-09-17

5. Improving scalability of parallel CNN training by adaptively adjusting parameter update frequency;Journal of Parallel and Distributed Computing;2022-01

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