Robust LassoNet: Enhancing Feature Selection in Neural Networks via Robust Loss Functions

arXiv:2609.38263 · stat.ML, cs.LG, math.PR · Submitted 2026-09-29 · Read on arXiv

stat.ML, cs.LG, math.PR

Submitted: 2026-09-29

Updated: 2026-10-09

Code: https://github.com/paola-stolfi/Robust-LassoNet

Project page: https://lasso-net.github.io

Terminology

• Loss Function — 39× in this paper · explained in 2 episodes
• Sparsity — 26× in this paper · explained in 4 episodes
• Feature Selection — 25× in this paper · explained in 4 episodes
• Benchmark — 20× in this paper · explained in 2 episodes
• Robustness — 19× in this paper · explained in 5 episodes
• Regularization — 17× in this paper · explained in 3 episodes
• Accuracy — 15× in this paper · explained in 1 episode
• Core — 9× in this paper · explained in 2 episodes
• Interpretability — 9× in this paper · explained in 15 episodes
• Mean Squared Error — 6× in this paper
• Consistency — 5× in this paper · explained in 3 episodes
• Pruning — 4× in this paper · explained in 4 episodes
• Generalization — 3× in this paper · explained in 13 episodes
• False Negative Rate — 2× in this paper
• Influence Functions — 2× in this paper · explained in 2 episodes
• Number of Selected Rate — 2× in this paper
• Objective Function — 2× in this paper · explained in 2 episodes
• Steering — 2× in this paper · explained in 2 episodes
• Activation Function — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Computational Tractability — 1× in this paper · explained in 2 episodes
• False Positive Rate — 1× in this paper
• Least Absolute Shrinkage and Selection Operator — 1× in this paper
• Predictive Mean Squared Error — 1× in this paper
• Predictive Modeling — 1× in this paper · explained in 2 episodes

Sources

• Sparse-Input Neural Networks for High-dimensional Nonparametric Regression and Classification
• Risk Bounds for Robust Deep Learning
• Robust Nonparametric Regression with Deep Neural Networks
• Semiparametric M-estimation with overparameterized neural networks

Related papers

• Behavior of prediction performance metrics with rare events
• Optimal Estimation of Generic Dynamics by Path-Dependent Neural Jump ODEs
• A Posterior-Dynamics Framework for Imaging Inverse Problems with Pretrained Diffusion Priors
• Efficient quadratic entropy with distance sketches
• Embedding-Bias in Conditional Independence Testing
• From Log-Odds to Shapley Values: An Explanatory Geometry for the Weighted Naive Bayes Classifier