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#machine learning Preprint Sep 2026

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 selection. However, i...

D. De Canditiis, I. De Feis, P. Stolfi · 0 citations

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