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2002.11097
Cited By
Problems with Shapley-value-based explanations as feature importance measures
25 February 2020
Indra Elizabeth Kumar
Suresh Venkatasubramanian
C. Scheidegger
Sorelle A. Friedler
TDI
FAtt
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Papers citing
"Problems with Shapley-value-based explanations as feature importance measures"
50 / 86 papers shown
Title
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From Abstract to Actionable: Pairwise Shapley Values for Explainable AI
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Suboptimal Shapley Value Explanations
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Kernel Banzhaf: A Fast and Robust Estimator for Banzhaf Values
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38
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11 Jun 2024
Partial Information Decomposition for Data Interpretability and Feature Selection
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Stephen Hailes
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45
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29 May 2024
KernelSHAP-IQ: Weighted Least-Square Optimization for Shapley Interactions
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48
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17 May 2024
Interpretable Prediction and Feature Selection for Survival Analysis
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41
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23 Apr 2024
How should AI decisions be explained? Requirements for Explanations from the Perspective of European Law
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62
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RankingSHAP -- Listwise Feature Attribution Explanations for Ranking Models
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42
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Information-Theoretic State Variable Selection for Reinforcement Learning
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Efficient Shapley Performance Attribution for Least-Squares Regression
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23
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30 Oct 2023
Farzi Data: Autoregressive Data Distillation
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Zexue He
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Jianmo Ni
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Statistically Valid Variable Importance Assessment through Conditional Permutations
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48
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19 Apr 2023
Data-OOB: Out-of-bag Estimate as a Simple and Efficient Data Value
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41
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S. Deyne
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13
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Derivative-based Shapley value for global sensitivity analysis and machine learning explainability
Hui Duan
G. Ökten
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39
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24 Mar 2023
Feature Importance: A Closer Look at Shapley Values and LOCO
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53
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Trust Explanations to Do What They Say
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33
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14 Feb 2023
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Thore Gerlach
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Nico Piatkowski
29
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22 Jan 2023
Estimate Deformation Capacity of Non-Ductile RC Shear Walls using Explainable Boosting Machine
Z. Deger
Gülsen Taskin Kaya
J. Wallace
18
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11 Jan 2023
Impossibility Theorems for Feature Attribution
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Natasha Jaques
Pang Wei Koh
Been Kim
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27
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Interpretable models for extrapolation in scientific machine learning
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J. Saal
B. Meredig
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James H. Martin
26
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Measuring the Driving Forces of Predictive Performance: Application to Credit Scoring
Hué Sullivan
Hurlin Christophe
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A Time Series Approach to Explainability for Neural Nets with Applications to Risk-Management and Fraud Detection
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Model free variable importance for high dimensional data
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Masayoshi Mase
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34
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Extending the Neural Additive Model for Survival Analysis with EHR Data
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Sun-Young Yang
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17
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Greedy Modality Selection via Approximate Submodular Maximization
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Predicting Swarm Equatorial Plasma Bubbles via Machine Learning and Shapley Values
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16
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Interpretable (not just posthoc-explainable) medical claims modeling for discharge placement to prevent avoidable all-cause readmissions or death
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Ted L. Chang
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Joe Maisog
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42
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Statistical Aspects of SHAP: Functional ANOVA for Model Interpretation
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FAtt
32
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Unifying local and global model explanations by functional decomposition of low dimensional structures
M. Hiabu
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Marvin N. Wright
FAtt
37
20
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Leveraging Explanations in Interactive Machine Learning: An Overview
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31
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Combining Counterfactuals With Shapley Values To Explain Image Models
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34
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Use-Case-Grounded Simulations for Explanation Evaluation
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