A survey of algorithmic recourse: definitions, formulations, solutions, and prospects

8 October 2020

Gilles Barthe

Papers citing "A survey of algorithmic recourse: definitions, formulations, solutions, and prospects"

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Title
Incentive-Aware Machine Learning; Robustness, Fairness, Improvement & Causality Chara Podimata 81 0 0 08 May 2025
Understanding Fixed Predictions via Confined Regions Connor Lawless Tsui-Wei Weng Berk Ustun Madeleine Udell 67 0 0 22 Feb 2025
ExpProof : Operationalizing Explanations for Confidential Models with ZKPs Chhavi Yadav Evan Monroe Laufer Dan Boneh Kamalika Chaudhuri 106 0 0 06 Feb 2025
Feature Responsiveness Scores: Model-Agnostic Explanations for Recourse Seung Hyun Cheon Anneke Wernerfelt Sorelle A. Friedler Berk Ustun FaML FAtt 119 1 0 29 Oct 2024
S-CFE: Simple Counterfactual Explanations Shpresim Sadiku Moritz Wagner Sai Ganesh Nagarajan Sebastian Pokutta 78 0 0 21 Oct 2024
HR-Bandit: Human-AI Collaborated Linear Recourse Bandit Junyu Cao Ruijiang Gao Esmaeil Keyvanshokooh 100 1 0 18 Oct 2024
Unifying Perspectives: Plausible Counterfactual Explanations on Global, Group-wise, and Local Levels Patryk Wielopolski Oleksii Furman Łukasz Lenkiewicz Jerzy Stefanowski Maciej Ziȩba 44 0 0 27 May 2024
Generating Likely Counterfactuals Using Sum-Product Networks Jiri Nemecek Tomás Pevný Georgios Korpas TPM 81 0 0 25 Jan 2024
Fairness in Machine Learning L. Oneto Silvia Chiappa FaML 272 493 0 31 Dec 2020
Beyond Individualized Recourse: Interpretable and Interactive Summaries of Actionable Recourses Kaivalya Rawal Himabindu Lakkaraju 34 11 0 15 Sep 2020
Model extraction from counterfactual explanations Ulrich Aïvodji Alexandre Bolot Sébastien Gambs MIACV MLAU 43 51 0 03 Sep 2020
Counterfactual Explanations for Machine Learning on Multivariate Time Series Data E. Ates Burak Aksar V. Leung A. Coskun AI4TS 87 67 0 25 Aug 2020
PermuteAttack: Counterfactual Explanation of Machine Learning Credit Scorecards Masoud Hashemi Ali Fathi AAML 31 32 0 24 Aug 2020
DECE: Decision Explorer with Counterfactual Explanations for Machine Learning Models Furui Cheng Yao Ming Huamin Qu CML HAI 18 101 0 19 Aug 2020
Counterfactual Explanation Based on Gradual Construction for Deep Networks Hong G Jung Sin-Han Kang Hee-Dong Kim Dong-Ok Won Seong-Whan Lee OOD FAtt 42 23 0 05 Aug 2020
Geometrically Enriched Latent Spaces Georgios Arvanitidis Søren Hauberg Bernhard Schölkopf DRL 43 53 0 02 Aug 2020
Fast Real-time Counterfactual Explanations Yunxia Zhao 27 15 0 11 Jul 2020
Machine Learning Explainability for External Stakeholders Umang Bhatt Mckane Andrus Adrian Weller Alice Xiang FaML SILM 24 58 0 10 Jul 2020
Counterfactual explanation of machine learning survival models M. Kovalev Lev V. Utkin CML OffRL 63 19 0 26 Jun 2020
On Counterfactual Explanations under Predictive Multiplicity Martin Pawelczyk Klaus Broelemann Gjergji Kasneci 102 85 0 23 Jun 2020
Algorithmic recourse under imperfect causal knowledge: a probabilistic approach Amir-Hossein Karimi Julius von Kügelgen Bernhard Schölkopf Isabel Valera CML 94 179 0 11 Jun 2020
Good Counterfactuals and Where to Find Them: A Case-Based Technique for Generating Counterfactuals for Explainable AI (XAI) Mark T. Keane Barry Smyth CML 54 146 0 26 May 2020
An ASP-Based Approach to Counterfactual Explanations for Classification Leopoldo Bertossi CML 39 15 0 28 Apr 2020
Multi-Objective Counterfactual Explanations Susanne Dandl Christoph Molnar Martin Binder B. Bischl 50 252 0 23 Apr 2020
SCOUT: Self-aware Discriminant Counterfactual Explanations Pei Wang Nuno Vasconcelos FAtt 38 82 0 16 Apr 2020
Plausible Counterfactuals: Auditing Deep Learning Classifiers with Realistic Adversarial Examples Alejandro Barredo Arrieta Javier Del Ser AAML 78 22 0 25 Mar 2020
Causal Interpretability for Machine Learning -- Problems, Methods and Evaluation Raha Moraffah Mansooreh Karami Ruocheng Guo A. Raglin Huan Liu CML ELM XAI 45 216 0 09 Mar 2020
ViCE: Visual Counterfactual Explanations for Machine Learning Models Oscar Gomez Steffen Holter Jun Yuan E. Bertini AAML 69 96 0 05 Mar 2020
Algorithmic Recourse: from Counterfactual Explanations to Interventions Amir-Hossein Karimi Bernhard Schölkopf Isabel Valera CML 40 340 0 14 Feb 2020
Convex Density Constraints for Computing Plausible Counterfactual Explanations André Artelt Barbara Hammer 28 47 0 12 Feb 2020
Distal Explanations for Model-free Explainable Reinforcement Learning Prashan Madumal Tim Miller L. Sonenberg F. Vetere FAtt LRM 28 25 0 28 Jan 2020
Black Box Explanation by Learning Image Exemplars in the Latent Feature Space Riccardo Guidotti A. Monreale Stan Matwin D. Pedreschi FAtt 65 67 0 27 Jan 2020
Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers Divyat Mahajan Chenhao Tan Amit Sharma OOD CML 82 206 0 06 Dec 2019
EMAP: Explanation by Minimal Adversarial Perturbation M. Chapman-Rounds Marc-Andre Schulz Erik Pazos K. Georgatzis AAML FAtt 20 6 0 02 Dec 2019
Causality for Machine Learning Bernhard Schölkopf CML AI4CE LRM 59 455 0 24 Nov 2019
PRINCE: Provider-side Interpretability with Counterfactual Explanations in Recommender Systems Azin Ghazimatin Oana Balalau Rishiraj Saha Roy Gerhard Weikum FAtt 36 99 0 19 Nov 2019
On the computation of counterfactual explanations -- A survey André Artelt Barbara Hammer LRM 36 50 0 15 Nov 2019
"How do I fool you?": Manipulating User Trust via Misleading Black Box Explanations Himabindu Lakkaraju Osbert Bastani 39 251 0 15 Nov 2019
Imperceptible Adversarial Attacks on Tabular Data Vincent Ballet X. Renard Jonathan Aigrain Thibault Laugel P. Frossard Marcin Detyniecki 47 72 0 08 Nov 2019
Synthesizing Action Sequences for Modifying Model Decisions Goutham Ramakrishnan Yun Chan Lee Aws Albarghouthi 94 33 0 30 Sep 2019
FACE: Feasible and Actionable Counterfactual Explanations Rafael Poyiadzi Kacper Sokol Raúl Santos-Rodríguez T. D. Bie Peter A. Flach 57 368 0 20 Sep 2019
Equalizing Recourse across Groups Vivek Gupta Pegah Nokhiz Chitradeep Dutta Roy Suresh Venkatasubramanian FaML 25 70 0 07 Sep 2019
Measurable Counterfactual Local Explanations for Any Classifier Adam White Artur Garcez FAtt 22 99 0 08 Aug 2019
Efficient computation of counterfactual explanations of LVQ models André Artelt Barbara Hammer 24 16 0 02 Aug 2019
Towards Realistic Individual Recourse and Actionable Explanations in Black-Box Decision Making Systems Shalmali Joshi Oluwasanmi Koyejo Warut D. Vijitbenjaronk Been Kim Joydeep Ghosh FaML 44 186 0 22 Jul 2019
The Dangers of Post-hoc Interpretability: Unjustified Counterfactual Explanations Thibault Laugel Marie-Jeanne Lesot Christophe Marsala X. Renard Marcin Detyniecki 31 195 0 22 Jul 2019
Why Does My Model Fail? Contrastive Local Explanations for Retail Forecasting Ana Lucic H. Haned Maarten de Rijke 52 63 0 17 Jul 2019
The What-If Tool: Interactive Probing of Machine Learning Models James Wexler Mahima Pushkarna Tolga Bolukbasi Martin Wattenberg F. Viégas Jimbo Wilson VLM 71 487 0 09 Jul 2019
Interpretable Counterfactual Explanations Guided by Prototypes A. V. Looveren Janis Klaise FAtt 43 380 0 03 Jul 2019
On the Privacy Risks of Model Explanations Reza Shokri Martin Strobel Yair Zick MIACV PILM SILM FAtt 20 36 0 29 Jun 2019