Advances in machine learning research drive progress in real-world applications. To ensure
this progress, it is important to understand the potential pitfalls on the way from a novel …

Self-supervision is often used for pre-training to foster performance on a downstream task by
constructing meaningful representations of samples. Self-supervised learning (SSL) …

Tabular Data is a mixture of numerical and categorical data, and machine learning models
have been evaluated to be more suitable than generative models in performing learning …

While contrastive learning (CL) has demonstrated success in image data, its application to
tabular data remains relatively unexplored. The effectiveness of CL heavily depends on data …

Contrastive learning has demonstrated significant potential across various domains,
including recent applications to tabular data. However, adapting this approach to tabular …

요 약 Tabular Data 는 수치형과 범주형 데이터의 혼합 데이터로, 이러한 Tabular Data 를
이용한 학습을 수행함에 있어, 주로 머신러닝 모델이생성형 모델보다 그 동안 적합하다고 …