Few-shot learning with adaptively initialized task optimizer: a practical meta-learning approach
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DOI: 10.1007/s10994-019-05838-7
Abstract: Considering the data collection and labeling cost in real-world applications, training a model with limited examples is an essential problem in machine learning, visual recognition, etc. Directly training a model on such few-shot learning (FSL)… read more here.
Keywords: shot learning; meta learning; task; adaptively initialized ... See more keywords