迁移学习(DDC)《Deep Domain Confusion: Maximizing for Domain Invariance》【已复现迁移】
论文信息
论文标题:Deep Domain Confusion: Maximizing for Domain Invariance
论文作者:Eric Tzeng, Judy Hoffman, Ning Zhang, Kate Saenko, Trevor Darrell
论文来源:arxiv 2014
论文地址:download
论文代码:download
引用次数:2203
1 介绍
域适应方法。
2 Method
模型框架:
目标函数:
$\operatorname{MMD}\left(X_{S}, X_{T}\right)= \quad\left\|\frac{1}{\left|X_{S}\right|} \sum_{x_{s} \in X_{S}} \phi\left(x_{s}\right)-\frac{1}{\left|X_{T}\right|} \sum_{x_{t} \in X_{T}} \phi\left(x_{t}\right)\right\|$
$\mathcal{L}=\mathcal{L}_{C}\left(X_{L}, y\right)+\lambda \operatorname{MMD}^{2}\left(X_{S}, X_{T}\right)$
因上求缘,果上努力~~~~ 作者:图神经网络,转载请注明原文链接:https://www.cnblogs.com/BlairGrowing/p/17066487.html