LG AI Research· EXAONE

[NeurIPS 2024 Series] Attention-Based Data Augmentation Techniques to Enhance Performance of Tabular Data Prediction

At NeurIPS 2024, the Table Representation Learning Workshop (TRL) , held for the third time this year, allowed researchers to focus on the representation learning of tabular data to exchange ideas. This year's TRL workshop saw 61 research papers accepted, a 1.5x increase from last year’s 41 papers, highlighting the growing attention being given to table data research. Table data is one of the most commonly used data formats in industry and everyday life, and global companies such as Amazon and Microsoft are actively conducting research in this area. At the NeurIPS 2024 TRL Workshop, LG AI Research's Data Intelligence (DI) Lab published a paper titled “AGATa: Attention-Guided Augmentation for Tabular Data in Contrastive Learning,” which was noted for its novel approach to improving training performance while maintaining the structural features of tabular data. LG AI Researchs’ AGATa: Attention-Guided Augmentation for Tabular Data in Contrastive Learning [8] Tabular data is a core data format in various industries such as finance, healthcare, and manufacturing. …

Announced

24 Jan 2025 00:00 UTC

Detected

28 Aug 2026 22:20 UTC (+581d after)