Learning Fair Rule Lists

Learning Fair Rule Lists

9 September 2019

Ulrich Aïvodji

Sébastien Gambs

Marie-José Huguet

Papers citing "Learning Fair Rule Lists"

17 / 17 papers shown

Title
"How do I fool you?": Manipulating User Trust via Misleading Black Box Explanations Himabindu Lakkaraju Osbert Bastani 46 252 0 15 Nov 2019
The Bouncer Problem: Challenges to Remote Explainability Erwan Le Merrer Gilles Tredan 33 8 0 03 Oct 2019
The Dangers of Post-hoc Interpretability: Unjustified Counterfactual Explanations Thibault Laugel Marie-Jeanne Lesot Christophe Marsala X. Renard Marcin Detyniecki 36 196 0 22 Jul 2019
Explanations can be manipulated and geometry is to blame Ann-Kathrin Dombrowski Maximilian Alber Christopher J. Anders M. Ackermann K. Müller Pan Kessel AAML FAtt 55 329 0 19 Jun 2019
Learning Optimal and Fair Decision Trees for Non-Discriminative Decision-Making S. Aghaei Javad Azizi P. Vayanos FaML 30 177 0 25 Mar 2019
Fooling Neural Network Interpretations via Adversarial Model Manipulation Juyeon Heo Sunghwan Joo Taesup Moon AAML FAtt 71 202 0 06 Feb 2019
Fairwashing: the risk of rationalization Ulrich Aïvodji Hiromi Arai O. Fortineau Sébastien Gambs Satoshi Hara Alain Tapp FaML 30 146 0 28 Jan 2019
The Frontiers of Fairness in Machine Learning Alexandra Chouldechova Aaron Roth FaML 130 415 0 20 Oct 2018
Learning Adversarially Fair and Transferable Representations David Madras Elliot Creager T. Pitassi R. Zemel FaML 323 678 0 17 Feb 2018
A comparative study of fairness-enhancing interventions in machine learning Sorelle A. Friedler C. Scheidegger Suresh Venkatasubramanian Sonam Choudhary Evan P. Hamilton Derek Roth FaML 88 639 0 13 Feb 2018
A Survey Of Methods For Explaining Black Box Models Riccardo Guidotti A. Monreale Salvatore Ruggieri Franco Turini D. Pedreschi F. Giannotti XAI 81 3,922 0 06 Feb 2018
Avoiding Discrimination through Causal Reasoning Niki Kilbertus Mateo Rojas-Carulla Giambattista Parascandolo Moritz Hardt Dominik Janzing Bernhard Schölkopf FaML CML 88 579 0 08 Jun 2017
Fairness in Criminal Justice Risk Assessments: The State of the Art R. Berk Hoda Heidari S. Jabbari Michael Kearns Aaron Roth 42 990 0 27 Mar 2017
Grad-CAM: Why did you say that? Ramprasaath R. Selvaraju Abhishek Das Ramakrishna Vedantam Michael Cogswell Devi Parikh Dhruv Batra FAtt 43 469 0 22 Nov 2016
Inherent Trade-Offs in the Fair Determination of Risk Scores Jon M. Kleinberg S. Mullainathan Manish Raghavan FaML 84 1,762 0 19 Sep 2016
The Mythos of Model Interpretability Zachary Chase Lipton FaML 123 3,672 0 10 Jun 2016
Certifying and removing disparate impact Michael Feldman Sorelle A. Friedler John Moeller C. Scheidegger Suresh Venkatasubramanian FaML 129 1,978 0 11 Dec 2014