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LMU Munich, Munich Center for Machine Learning
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Adaptive coalition selection in ShaplEIG boosts Shapley value estimation efficiency, slashing computational complexity and enhancing performance in resource-constrained settings.
ProxySHAP slashes the computational cost of Shapley interaction estimation while simultaneously boosting accuracy, finally making high-order interaction analysis practical for models with thousands of features.
Additive explanations of survival models fail because of their inherent non-additivity, but now there's a way to decompose feature interactions into time-dependent components to understand *when* and *why* they fail.