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Supervised Contrastive Learning
Created
2024-12-11
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Updated
2025-02-28
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ALTNT
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http://blog.705553939.xyz/2024/12/11/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E8%87%AA%E7%9B%91%E7%9D%A3/2021-supervised-contrastive-learning/
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Contents
1.
Supervised Contrastive Learning
1.1.
摘要
1.2.
1、介绍
1.3.
2、相关工作
1.4.
3、 方法
1.4.1.
3.1表示学习框架
1.4.2.
3.2对比损失函数
1.4.2.1.
3.2.1 自监督对比损失
1.4.2.2.
3.2.2监督对比损失
1.4.2.2.1.
1、 推广到任意数量的正样本：
1.4.2.2.2.
2、对比能力随着更多的负样本而增加：
1.4.2.2.3.
3、具有执行硬正样本/负样本挖掘的内在能力：
1.4.2.3.
3.2.3 与三元组损失和 N 对损失的关联(Triplet Loss and N-pairs Loss)
1.5.
4实验
1.5.1.
4.1 分类准确率
1.5.2.
4.2 对图像损坏和减少的训练数据的鲁棒性
1.5.3.
4.3 超参数稳定性
1.5.4.
4.4迁移学习
1.5.5.
4.5 训练细节
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