The Explanation Game: Explaining Machine Learning Models Using Shapley
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The Explanation Game: Explaining Machine Learning Models Using Shapley Values

17 September 2019

Ankur Taly

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Papers citing "The Explanation Game: Explaining Machine Learning Models Using Shapley Values"

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Title
AI Data Readiness Inspector (AIDRIN) for Quantitative Assessment of Data Readiness for AI Kaveen Hiniduma Suren Byna J. L. Bez Ravi Madduri 108 7 0 27 Jun 2024
Beyond the Black Box: Do More Complex Models Provide Superior XAI Explanations? Mateusz Cedro Marcin Chlebus 67 1 0 14 May 2024
How should AI decisions be explained? Requirements for Explanations from the Perspective of European Law Benjamin Frész Elena Dubovitskaya Danilo Brajovic Marco F. Huber Christian Horz 94 9 0 19 Apr 2024
A general-purpose method for applying Explainable AI for Anomaly Detection John Sipple Abdou Youssef 85 17 0 23 Jul 2022
Interpretable Data-Based Explanations for Fairness Debugging Romila Pradhan Jiongli Zhu Boris Glavic Babak Salimi 91 57 0 17 Dec 2021
Reward-Reinforced Reinforcement Learning for Multi-agent Systems Changgang Zheng Shufan Yang Juan Marcelo Parra Ullauri A. García-Domínguez Nelly Bencomo 39 10 0 22 Mar 2021
Explaining Black-Box Algorithms Using Probabilistic Contrastive Counterfactuals Sainyam Galhotra Romila Pradhan Babak Salimi CML 105 110 0 22 Mar 2021
Selective Intervention Planning using Restless Multi-Armed Bandits to Improve Maternal and Child Health Outcomes Siddharth Nishtala Lovish Madaan Aditya Mate Harshavardhan Kamarthi Anirudh Grama ... Ramesh Padmanabhan Aparna Hegde Pradeep Varakantham Balaraman Ravindran Milind Tambe 39 9 0 07 Mar 2021
Shapley values for feature selection: The good, the bad, and the axioms D. Fryer Inga Strümke Hien Nguyen FAtt TDI 105 205 0 22 Feb 2021
Explaining by Removing: A Unified Framework for Model Explanation Ian Covert Scott M. Lundberg Su-In Lee FAtt 144 252 0 21 Nov 2020
Feature Removal Is a Unifying Principle for Model Explanation Methods Ian Covert Scott M. Lundberg Su-In Lee FAtt 138 33 0 06 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 118 154 0 03 Nov 2020
Principles and Practice of Explainable Machine Learning Vaishak Belle I. Papantonis FaML 81 452 0 18 Sep 2020
Explaining the data or explaining a model? Shapley values that uncover non-linear dependencies D. Fryer Inga Strümke Hien Nguyen TDI FAtt 63 7 0 12 Jul 2020
An exploration of the influence of path choice in game-theoretic attribution algorithms Geoff Ward S. Kamkar Jay Budzik TDI FAtt 21 1 0 08 Jul 2020
Missed calls, Automated Calls and Health Support: Using AI to improve maternal health outcomes by increasing program engagement Siddharth Nishtala Harshavardhan Kamarthi D. Thakkar Dhyanesh Narayanan Anirudh Grama ... Ramesh Padmanabhan N. Madhiwalla S. Chaudhary Balaraman Ravindran Milind Tambe 41 16 0 13 Jun 2020
Problems with Shapley-value-based explanations as feature importance measures Indra Elizabeth Kumar Suresh Venkatasubramanian C. Scheidegger Sorelle A. Friedler TDI FAtt 106 369 0 25 Feb 2020