Explaining Preferences with Shapley Values

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Explaining Preferences with Shapley Values

26 May 2022

Jaime Ferrando Huertas

Dino Sejdinovic

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Papers citing "Explaining Preferences with Shapley Values"

12 / 12 papers shown

Title
Efficient Hyperparameter Tuning for Large Scale Kernel Ridge Regression Giacomo Meanti Luigi Carratino Ernesto De Vito Lorenzo Rosasco 53 13 0 17 Jan 2022
RKHS-SHAP: Shapley Values for Kernel Methods Siu Lun Chau Robert Hu Javier I. González Dino Sejdinovic FAtt 60 20 0 18 Oct 2021
On Locality of Local Explanation Models Sahra Ghalebikesabi Lucile Ter-Minassian Karla Diaz-Ordaz Chris Holmes FedML FAtt 60 40 0 24 Jun 2021
GraphSVX: Shapley Value Explanations for Graph Neural Networks Alexandre Duval Fragkiskos D. Malliaros FAtt 65 90 0 18 Apr 2021
Explaining by Removing: A Unified Framework for Model Explanation Ian Covert Scott M. Lundberg Su-In Lee FAtt 106 251 0 21 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 109 153 0 03 Nov 2020
True to the Model or True to the Data? Hugh Chen Joseph D. Janizek Scott M. Lundberg Su-In Lee TDI FAtt 153 166 0 29 Jun 2020
Learning Inconsistent Preferences with Gaussian Processes Siu Lun Chau Javier I. González Dino Sejdinovic 37 7 0 06 Jun 2020
Feature relevance quantification in explainable AI: A causal problem Dominik Janzing Lenon Minorics Patrick Blobaum FAtt CML 74 282 0 29 Oct 2019
Asymmetric Shapley values: incorporating causal knowledge into model-agnostic explainability Christopher Frye C. Rowat Ilya Feige 61 182 0 14 Oct 2019
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 1.2K 17,027 0 16 Feb 2016
Universality, Characteristic Kernels and RKHS Embedding of Measures Bharath K. Sriperumbudur Kenji Fukumizu Gert R. G. Lanckriet 224 531 0 03 Mar 2010