QuadraSHAP: $\epsilon$-Exact Shapley Values for Product Games in Logarithmic Parallel Time

תקציר מקורי באנגליתarXiv:2605.05870v4 Announce Type: replace Abstract: We introduce QuadraSHAP, a method for $\epsilon$-exact Shapley computation in product games, cooperative games whose coalition values factorize across players. Given a tolerance $\epsilon\ge0$, the method determines a computational budget before evaluation, guaranteeing an absolute attribution error of at most $\epsilon$ for every feature in exact arithmetic. By extending to weighted sums of product games, the framework supports baseline and empirical interventional attribution across a broad class of models, including log-link regression models, Cox proportional-hazards models, odds-scale classifiers, product-kernel machines, and tree-based models. For a $d$-player product game, we replace the exponentially large coalition sum by a one-d