Exploring Complementary Strengths of Invariant and Equivariant Representations for Few-Shot Learning
Exploring Complementary Strengths of Invariant and Equivariant Representations for Few-Shot Learning
In many real-world problems, collecting a large number of labeled samples is infeasible. Few-shot learning (FSL) is the dominant approach to address this issue, where the objective is to quickly adapt to novel categories in presence of a limited number of samples. FSL tasks have been predominantly solved by leveraging …