Elnaz Barshan

RelatIF: Identifying Explanatory Training Samples via Relative Influence

In this work, we focus on the use of influence functions to identify relevant training examples that one might hope “explain” the predictions of a machine learning model. One shortcoming of influence functions is that the training examples deemed most “influential” are often outliers or mislabelled,…