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Robust LassoNet: Enhancing Feature Selection in Neural Networks via Robust Loss Functions
Feature selection in neural networks remains a challenging problem, particularly in the presence of noisy or contaminated data. LassoNet is a recent approach that addresses this issue by combining neural networks with hierarchical sparsity constraints, enabling simultaneous prediction and variable s
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