11 papers
An Odd Estimator for Shapley Values
Fabian Fumagalli, Landon Butler, Justin Singh Kang +2
The Shapley value is a ubiquitous framework for attribution in machine learning, encompassing feature importance, data valuation, and causal inference. However, its exact computati…
Proxy-Based Approximation of Shapley and Banzhaf Interactions
Santo M. A. R. Thies, Hubert Baniecki, R. Teal Witter +3
Shapley and Banzhaf interactions capture the complex dynamics inherent in modern machine learning applications. However, current estimators for these higher-order interactions trad…
SEAL: Semantic Aware Image Watermarking
Kasra Arabi, R. Teal Witter, Chinmay Hegde +1
Generative models have rapidly evolved to generate realistic outputs. However, their synthetic outputs increasingly challenge the clear distinction between natural and AI-generated…
PolySHAP: Extending KernelSHAP with Interaction-Informed Polynomial Regression
Fabian Fumagalli, R. Teal Witter, Christopher Musco
Shapley values have emerged as a central game-theoretic tool in explainable AI (XAI). However, computing Shapley values exactly requires game evaluations for a model with …
Exactly Computing do-Shapley Values
R. Teal Witter, Ãlvaro Parafita, Tomas Garriga +4
Structural Causal Models (SCM) are a powerful framework for describing complicated dynamics across the natural sciences. A particularly elegant way of interpreting SCMs is do-Shapl…
Regression-adjusted Monte Carlo Estimators for Shapley Values and Probabilistic Values
R. Teal Witter, Yurong Liu, Christopher Musco
With origins in game theory, probabilistic values like Shapley values, Banzhaf values, and semi-values have emerged as a central tool in explainable AI. They are used for feature a…