A review that organizes RL-based and generative methods for tabular feature selection and generation into a taxonomy, compares their strengths and limitations, and outlines research challenges.
Efficient reinforced fea- ture selection via early stopping traverse strategy
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A Survey on Data-Centric AI: Tabular Learning from Reinforcement Learning and Generative AI Perspective
A review that organizes RL-based and generative methods for tabular feature selection and generation into a taxonomy, compares their strengths and limitations, and outlines research challenges.