Integrated Feature Selection for classification and Representation Learning with Group-Lasso Siamese Networks
arXiv:2610.39499v1 Announce Type: new Abstract: The Least Absolute Shrinkage and Selection Operator (Lasso) has been widely employed for feature selection in linear models and has also been extended to multi-layer perceptron (MLP) networks for both feature and group feature selection. Group-Lasso has also been used in feature selection using feed-forward neural networks. To the best of our knowledge, this is the first study to incorporate the Group-Lasso principle into a Siamese network archite…