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Fréchet regression for multi-label feature selection with implicit regularization
Fr\'echet regression extends linear regression to model complex responses in metric spaces, making it particularly relevant for multi-label regression, where each instance can have multiple associated labels.
Implicit Regularization for Multi-label Feature Selection
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.
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