SCAD
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Related Articles from SNS
Implicit Regularization for Multi-label Feature Selection
arXiv:2411.11436v2 Announce Type: replace Abstract: In this paper, we address the problem of feature selection in the context of multi-label learning, by using a new estimator based on implicit regularization and label embedding. Unlike the sparse feature selection methods that use a penalized estimator with explicit regularization terms such as $l_{2,1}$-norm, MCP or SCAD, we propose a simple alternative method via Hadamard product parameterization. In order to guide the feature selection...