Web: http://arxiv.org/abs/2206.10137

June 23, 2022, 1:11 a.m. | Ali Lotfi Rezaabad, Sidharth Kumar, Sriram Vishwanath, Jonathan I. Tamir

cs.LG updates on arXiv.org arxiv.org

Contrastive self-supervised learning methods learn to map data points such as
images into non-parametric representation space without requiring labels. While
highly successful, current methods require a large amount of data in the
training phase. In situations where the target training set is limited in size,
generalization is known to be poor. Pretraining on a large source data set and
fine-tuning on the target samples is prone to overfitting in the few-shot
regime, where only a small number of target samples …

arxiv cv domain adaptation learning representation representation learning unsupervised

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