Loss factorization, weakly supervised learning and label noise robustness

Giorgio Patrini, Frank Nielsen, Richard Nock, Marcello Carioni

Abstract: We prove that the empirical risk of most well-known loss functions factors into a linear term aggregating all labels with a term that is label free, and can further be expressed by sums of the same...