Xiang Ye

Revisit Finetuning strategy for Few-Shot Learning to Transfer the Emdeddings

Few-Shot Learning (FSL) aims to learn a simple and effective bias on limited novel samples. Recently, many methods have been focused on re-training a randomly initialized linear classifier to adapt it to the novel features extracted by the pre-trained feature extractor (called Linear-Probing-based m…