Our paper on "Robust penalized estimators for high-dimensional
generalized linear models" is accepted in TEST, see it at https://link.springer.com/article/10.1007/s11749-025-00978-6
or in arXiv at https://arxiv.org/abs/2312.04661
#HighDimension
#GeneralizedLinearModels
#PenalizedMethods
#RobustStatistics
#MT-Estimators

I am surprised this paper received so little attention. It dramatically reduces RAM requirements for very big #statistical #generalizedlinearmodels while offering #computational speed ups ~x500. A #recommender system used it in a #neuralnetwork with #tensorflow to get substantial time & memory savings.
https://arxiv.org/abs/2205.13080
Languages with #array/ #tensor features should take note, as this is a serious contender to sparse matrix computations #datascience #machinelearning
https://mstdn.science/@ChristosArgyrop/110934217550435224