Large-Margin Softmax Loss for Convolutional Neural Networks
L-Sofmax paper url: https://arxiv.org/pdf/1612.02295 year:2017 Introduction 交叉熵损失与softmax一起使用可以说是CNN中最常用的监督组件之一。 尽管该组件简单而且性能出色, 但是它只要求特征的可分性, 没有明确鼓励网络学习到的特征具有类内方差小, 类间方差大的特性。 该文中，作者提出了一个广义的 large marg
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相关文章
- 1. Large-Margin Softmax Loss for Convolutional Neural Networks
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- 4. Bag of Tricks for Convolutional Neural Networks
- 5. Convolutional Neural Networks: Application
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- 7. Large-Margin Softmax Loss
- 8. Convolutional Neural Networks for Visual Recognition
- 9. 《Convolutional Neural Networks for Sentence Classification》
- 10. Recurrent Convolutional Neural Networks for Text Classification