【论文阅读】Gradient Centralization: A New Optimization Technique for Deep Neural Networks
香港理工&阿里达摩院新做，操做优雅，一行代码嵌入优化器提高性能！git ArXiv 连接：https://arxiv.org/abs/2004.01461github Github 连接：https://github.com/Yonghongwei/Gradient-Centralization算法 1、摘要 优化技术对有效地训练深度神经网络 (DNN) 而言具备重要意义。结果代表，利用一阶和二
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相关文章
- 1. 【论文阅读】Gradient Centralization: A New Optimization Technique for Deep Neural Networks
- 2. Gradient Centralization: A New Optimization Technique for Deep Neural Networks（讲解）
- 3. 论文阅读：Deep Neural Networks for Object Detection
- 4. [论文解读] Concolic Testing for Deep Neural Networks
- 5. 【论文阅读】[2009.00278v2]Scaling Up Deep Neural Network Optimization for Edge Inference
- 6. 论文阅读-Fast Algorithms for Convolutional Neural Networks
- 7. 论文阅读：Aggregated Residual Transformations for Deep Neural Networks（ResNeXt）
- 8. 论文阅读：《Convolutional Neural Networks for Sentence Classification》
- 9. 论文阅读--PVANET: Deep but Lightweight Neural Networks for Real-time Object Detection
- 10. [论文阅读]ResNetXt|Aggregated Residual Transformations for Deep Neural Networks