Problems with Shapley-value-based explanations as feature importance measures

25 February 2020

Indra Elizabeth Kumar

Suresh Venkatasubramanian

Papers citing "Problems with Shapley-value-based explanations as feature importance measures"

36 / 86 papers shown

Title
Towards a Responsible AI Development Lifecycle: Lessons From Information Security Erick Galinkin SILM 21 6 0 06 Mar 2022
The Shapley Value in Machine Learning Benedek Rozemberczki Lauren Watson Péter Bayer Hao-Tsung Yang Oliver Kiss Sebastian Nilsson Rik Sarkar TDI FAtt 32 206 0 11 Feb 2022
Explainability in Music Recommender Systems Darius Afchar Alessandro B. Melchiorre Markus Schedl Romain Hennequin Elena V. Epure Manuel Moussallam 39 48 0 25 Jan 2022
Prolog-based agnostic explanation module for structured pattern classification Gonzalo Nápoles Fabian Hoitsma A. Knoben A. Jastrzębska Maikel Leon Espinosa 25 13 0 23 Dec 2021
AcME -- Accelerated Model-agnostic Explanations: Fast Whitening of the Machine-Learning Black Box David Dandolo Chiara Masiero Mattia Carletti Davide Dalle Pezze Gian Antonio Susto FAtt LRM 24 23 0 23 Dec 2021
Exact Shapley Values for Local and Model-True Explanations of Decision Tree Ensembles Thomas W. Campbell H. Roder R. Georgantas J. Roder FedML TDI FAtt 24 16 0 16 Dec 2021
Designing Inherently Interpretable Machine Learning Models Agus Sudjianto Aijun Zhang FaML 19 31 0 02 Nov 2021
Counterfactual Shapley Additive Explanations Emanuele Albini Jason Long Danial Dervovic Daniele Magazzeni 31 49 0 27 Oct 2021
Self-explaining Neural Network with Concept-based Explanations for ICU Mortality Prediction Sayantan Kumar Sean C. Yu Thomas Kannampallil Zachary B. Abrams Andrew Michelson Philip R. O. Payne FAtt 19 7 0 09 Oct 2021
Robotic Lever Manipulation using Hindsight Experience Replay and Shapley Additive Explanations Sindre Benjamin Remman A. Lekkas 28 14 0 07 Oct 2021
Fast TreeSHAP: Accelerating SHAP Value Computation for Trees Jilei Yang FAtt 38 35 0 20 Sep 2021
Model Explanations via the Axiomatic Causal Lens Gagan Biradar Vignesh Viswanathan Yair Zick XAI CML 25 1 0 08 Sep 2021
Instance-wise or Class-wise? A Tale of Neighbor Shapley for Concept-based Explanation Jiahui Li Kun Kuang Lin Li Long Chen Songyang Zhang Jian Shao Jun Xiao FAtt 20 18 0 03 Sep 2021
What will it take to generate fairness-preserving explanations? Jessica Dai Sohini Upadhyay Stephen H. Bach Himabindu Lakkaraju FAtt FaML 26 14 0 24 Jun 2021
Rational Shapley Values David S. Watson 25 20 0 18 Jun 2021
FairCanary: Rapid Continuous Explainable Fairness Avijit Ghosh Aalok Shanbhag Christo Wilson 13 20 0 13 Jun 2021
On the Lack of Robust Interpretability of Neural Text Classifiers Muhammad Bilal Zafar Michele Donini Dylan Slack Cédric Archambeau Sanjiv Ranjan Das K. Kenthapadi AAML 16 21 0 08 Jun 2021
Shapley Counterfactual Credits for Multi-Agent Reinforcement Learning Jiahui Li Kun Kuang Baoxiang Wang Furui Liu Long Chen Fei Wu Jun Xiao OffRL 27 60 0 01 Jun 2021
SHAQ: Incorporating Shapley Value Theory into Multi-Agent Q-Learning Jianhong Wang Yuan Zhang Yunjie Gu Tae-Kyun Kim OffRL FAtt 22 19 0 31 May 2021
Cohort Shapley value for algorithmic fairness Masayoshi Mase Art B. Owen Benjamin B. Seiler 26 14 0 15 May 2021
Winter wheat yield prediction using convolutional neural networks from environmental and phenological data A. Srivastava N. Safaei S. Khaki Gina M. Lopez W. Zeng F. Ewert T. Gaiser Jaber Rahimi 39 100 0 04 May 2021
Towards Rigorous Interpretations: a Formalisation of Feature Attribution Darius Afchar Romain Hennequin Vincent Guigue FAtt 40 20 0 26 Apr 2021
Local Explanations via Necessity and Sufficiency: Unifying Theory and Practice David S. Watson Limor Gultchin Ankur Taly Luciano Floridi 22 63 0 27 Mar 2021
Explaining Black-Box Algorithms Using Probabilistic Contrastive Counterfactuals Sainyam Galhotra Romila Pradhan Babak Salimi CML 30 105 0 22 Mar 2021
Ensembles of Random SHAPs Lev V. Utkin A. Konstantinov FAtt 21 20 0 04 Mar 2021
Contrastive Explanations for Model Interpretability Alon Jacovi Swabha Swayamdipta Shauli Ravfogel Yanai Elazar Yejin Choi Yoav Goldberg 49 95 0 02 Mar 2021
Shapley values for feature selection: The good, the bad, and the axioms D. Fryer Inga Strümke Hien Nguyen FAtt TDI 16 190 0 22 Feb 2021
Outcome-Explorer: A Causality Guided Interactive Visual Interface for Interpretable Algorithmic Decision Making Md. Naimul Hoque Klaus Mueller CML 59 30 0 03 Jan 2021
Interpretability and Explainability: A Machine Learning Zoo Mini-tour Ricards Marcinkevics Julia E. Vogt XAI 33 119 0 03 Dec 2020
Explaining by Removing: A Unified Framework for Model Explanation Ian Covert Scott M. Lundberg Su-In Lee FAtt 53 243 0 21 Nov 2020
Towards Unifying Feature Attribution and Counterfactual Explanations: Different Means to the Same End R. Mothilal Divyat Mahajan Chenhao Tan Amit Sharma FAtt CML 32 100 0 10 Nov 2020
Causal Shapley Values: Exploiting Causal Knowledge to Explain Individual Predictions of Complex Models Tom Heskes E. Sijben I. G. Bucur Tom Claassen FAtt TDI 25 151 0 03 Nov 2020
Interpretable Machine Learning -- A Brief History, State-of-the-Art and Challenges Christoph Molnar Giuseppe Casalicchio B. Bischl AI4TS AI4CE 28 396 0 19 Oct 2020
On the Tractability of SHAP Explanations Guy Van den Broeck A. Lykov Maximilian Schleich Dan Suciu FAtt TDI 22 260 0 18 Sep 2020
Predictive Multiplicity in Classification Charles Marx Flavio du Pin Calmon Berk Ustun 36 136 0 14 Sep 2019
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 259 3,698 0 28 Feb 2017