Thresholding Data Shapley for Data Cleansing Using Multi-Armed Bandits

Data cleansing aims to improve model performance by removing a set of harmful instances from the training dataset. Data Shapley is a common theoretically guaranteed method to evaluate the contribution of each instance to model performance; however, it requires training on all subsets of the training data, which is computationally expensive. In this paper, we propose an iterativemethod to fast identify a subset of instances with low data Shapley values by using the thresholding bandit algorithm. We provide a theoretical …

cs.ai cs.lg data data cleansing dataset instance instances multi-armed bandits performance set thresholding training training data