Hosik Choi — accepted AI-conference papers

2026

TabularBERT: Binning-Based Self-Supervised Learning for Tabular Representation

Beomjin Park, Seunghwan An, Sungchul Hong, Hosik Choi

ICML 2026poster

Tabular data is one of the most fundamental and widely used formats for representing structured information. Classical machine learning algorithms continue to achieve substantial success in extracting predictive patterns and constructing accurate models from structured data; however, representation …

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2023

BlackVIP: Black-Box Visual Prompting for Robust Transfer Learning

Changdae Oh, Hyeji Hwang, Hee-young Lee, YongTaek Lim, Geunyoung Jung, Jiyoung Jung +2

CVPR 2023poster

With the surge of large-scale pre-trained models (PTMs), fine-tuning these models to numerous downstream tasks becomes a crucial problem. Consequently, parameter efficient transfer learning (PETL) of large models has grasped huge attention. While recent PETL methods showcase impressive performance,…

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