The authors propose a novel approach to few-shot learning using meta-learning. Few-shot learning is a challenging problem in machine learning where a model must learn to classify new objects with only a small number of examples. The authors demonstrate the effectiveness of their approach by comparing it to several existing state-of-the-art methods for few-shot learning… Read More