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.
Beyond Discrete Se- lection: Continuous Embedding Space Optimization for Generative Feature Selection
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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.