Learning from Uncertain Data: From Possible Worlds to Possible Models

J Zhu, S Feng, B Glavic, B Salimi - arXiv preprint arXiv:2405.18549, 2024 - arxiv.org
We introduce an efficient method for learning linear models from uncertain data, where
uncertainty is represented as a set of possible variations in the data, leading to predictive …