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cs.LG2025
The Semantic Architect: How FEAML Bridges Structured Data and LLMs for Multi-Label Tasks
Wanfu Gao, Zebin He, Jun Gao
Existing feature engineering methods based on large language models (LLMs) have not yet been applied to multi-label learning tasks. They lack the ability to model complex label dep…
cs.LG2025
Graph Random Walk with Feature-Label Space Alignment: A Multi-Label Feature Selection Method
Wanfu Gao, Jun Gao, Qingqi Han +2
The rapid growth in feature dimension may introduce implicit associations between features and labels in multi-label datasets, making the relationships between features and labels…
cs.LG2025
Two-Stage Feature Generation with Transformer and Reinforcement Learning
Wanfu Gao, Zengyao Man, Zebin He +3
Feature generation is a critical step in machine learning, aiming to enhance model performance by capturing complex relationships within the data and generating meaningful new feat…