Add README.

BKL255 · Apr 6, 2019 · 6ce2abf · 6ce2abf
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@@ -2,4 +2,10 @@ This is a PyTorch implementation of the IJCNN 2019 paper:
 
 [Accelerating Deep Unsupervised Domain Adaptation with Transfer Channel Pruning](https://arxiv.org/abs/1904.02654)
 
+The contributions of this paper are summarized as follows.
+1. We present TCP as a unified approach for accelerating deep unsupervised domain adaptation models. TCP is a generic, accurate, and efficient compression method that can be easily implemented by most deep learning libraries.
+2. TCP is able to reduce negative transfer by considering the cross-domain distribution discrepancy using the proposed Transfer Channel Evaluation module.
+3. Extensive experiments on two public UDA datasets demonstrate the significant superiority of TCP.
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