DAN
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thuml
您好，请教一个问题，在《Learning Transferable Features with Deep Adaptation Networks》这篇论文中，在求解网络参数$theta$时，论文将第L层参数的梯度表示为：J（Zi）对第L层参数的偏导+gk（zli）对第L层参数的偏导，如果按照本文CNN的目标函数，第二项不应该是从L6-L8三层的gk和么？这里单独拿出来第L层的gk应该怎么理解？希望能得到您的指点，非常感谢！
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Steps to reproduce
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Your system configuration
Operating system: Compiler: CUDA version (if applicable): CUDNN version (if applicable): BLAS: Python or MATLAB version (for pycaffe and matcaffe respectively):
