When, Where, and How: Adaptive Binning for Tabular Self-Supervised Learning
Adaptive Binning introduces a training-adaptive discretization method for self-supervised learning on medical tabular data, improving representation learning through feature-wise r…
Hugging Face · Daily Papers
·Daehwan Kim, Haejun Chung
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·▲ 1 upvotes
Este artigo está em destaque na seleção diária de papers do Hugging Face, curada pela comunidade de pesquisa em IA.
Autores: Daehwan Kim, Haejun Chung, Ikbeom Jang
- 1 upvotes da comunidade
- Temas: self-supervised learning, tabular data, discretization, pretexts, spectral bias, curriculum learning
Resumo
Resumo original (em inglês), extraído do paper:
Adaptive Binning introduces a training-adaptive discretization method for self-supervised learning on medical tabular data, improving representation learning through feature-wise refinement and heterogeneous feature handling.
