Data Banzhaf: A Data Valuation Framework with Maximal Robustness to Learning Stochasticity. (arXiv:2205.15466v2 [cs.LG] UPDATED)

This paper studies the robustness of data valuation to noisy model
performance scores. Particularly, we find that the inherent randomness of the
widely used stochastic gradient descent can cause existing data value notions
(e.g., the Shapley value and the Leave-one-out error) to produce inconsistent
data value rankings across different runs. To address this challenge, we first
pose a formal framework within which one can measure the robustness of a data
value notion. We show that the Banzhaf value, a value …

arxiv data framework learning lg robustness valuation