Unverified50% confidenceFactExact time
Shapley values satisfy four axioms—efficiency, symmetry, dummy, and additivity—and are considered the theoretically fairest method of feature attribution.
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50%
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Long-term
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10/9/2026
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UnverifiedThe paper provides an analytical form of Shapley values for weighted naive Bayes (a closed-form analytical solution requiring no sampling).61% similarUnverifiedNoam Shazeer's SwiGLU activation function paper attributes the architecture's success to "divine benevolence" in the conclusion section60% similarUnverifiedThe theoretical basis of SHAP comes from the concept of Shapley values in cooperative game theory, proposed by Nobel Prize-winning economist Lloyd Shapley in 1953; in 2017, Lundberg and Lee introduced it into the field of machine learning.57% similarUnverifiedThe theoretical foundation of SHAP (SHapley Additive exPlanations) originates from the fair allocation scheme proposed by Lloyd Shapley in cooperative game theory, for which he received the Nobel Prize in Economics in 1953.56% similarUnverifiedNguyen and Stehlé proved that as long as the floating-point precision satisfies a dimension-dependent lower bound (approximately O(n) bits of floating-point mantissa precision), the correctness of each step of the LLL algorithm is guaranteed.56% similar
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