Learning from Uncertain Data: From Possible Worlds to Possible Models

Jiongli Zhu, Su Feng, Boris Glavic +1

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…