ModelPred: A Framework for Predicting Trained Model from Training Data

Yingyan Zeng, Jiachen T. Wang, Si Chen +3

In this work, we propose ModelPred, a framework that helps to understand the impact of changes in training data on a trained model. This is critical for building trust in various s…