AI RESEARCH
xRFM: Accurate, scalable, and interpretable feature learning models for tabular data
arXiv CS.LG
•
ArXi:2508.10053v3 Announce Type: replace Inference from tabular data, collections of continuous and categorical variables organized into matrices, is a foundation for modern technology and science. Yet, in contrast to the explosive changes in the rest of AI, the best practice for these predictive tasks has been relatively unchanged and is still primarily based on variations of Gradient Boosted Decision Trees (GBDTs