Domain Adaptive Transfer Learning with Specialist Models
arXiv: Computer Vision and Pattern Recognition, Volume abs/1811.07056, 2018.
Transfer learning is a widely used method to build high performing computer vision models. In this paper, we study the efficacy of transfer learning by examining how the choice of data impacts performance. We find that more pre-training data does not always help, and transfer performance depends on a judicious choice of pre-training data....More
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