Jul 2026
Directional Influence Function: Estimating Training Data Influence in Constrained Learning
DIF formulates the opti- mality conditions of constrained learning as a variational inequality (VI) and ana- lyzes how perturbing training data affects this VI, establishing DIF as an efficient and reliable tool for data attribution in constrained learning.
Xin Wang, R. Rockafellar, X. Ban
· arXiv.org · 0 citations