A Survey on Self-Supervised Learning for Non-Sequential Tabular Data

Self-supervised learning (SSL) has been incorporated into many state-of-the-art models in various domains, where SSL defines pretext tasks based on unlabeled datasets to learn contextualized and robust representations. Recently, SSL has been a new trend in exploring the representation learning capability in the realm of tabular data, which is more challenging due to not having explicit relations for learning descriptive representations. This survey aims to systematically review and summarize the recent progress and challenges of SSL for non-sequential tabular data …

art capability cs.ai cs.lg data datasets domains learn representation representation learning robust self-supervised learning ssl state state-of-the-art models supervised learning survey tabular tabular data tasks trend