The Bad Batches: Enhancing Self-Supervised Learning in Image Classification Through Representative Batch Curation

arXiv:2403.19579v1 Announce Type: new
Abstract: The pursuit of learning robust representations without human supervision is a longstanding challenge. The recent advancements in self-supervised contrastive learning approaches have demonstrated high performance across various representation learning challenges. However, current methods depend on the random transformation of training examples, resulting in some cases of unrepresentative positive pairs that can have a large impact on learning. This limitation not only impedes the convergence of the learning process but the robustness of the learnt representation …

abstract arxiv challenge challenges classification cs.cv curation current examples however human image performance random representation representation learning robust self-supervised learning supervised learning supervision through training transformation type