Learning What and Where to Transfer

15 May 2019Yunhun JangHankook LeeSung Ju HwangJinwoo Shin

As the application of deep learning has expanded to real-world problems with insufficient volume of training data, transfer learning recently has gained much attention as means of improving the performance in such small-data regime. However, when existing methods are applied between heterogeneous architectures and tasks, it becomes more important to manage their detailed configurations and often requires exhaustive tuning on them for the desired performance... (read more)

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