Amortized Generation of Sequential Algorithmic Recourses for Black-box Models

7 June 2021

Papers citing "Amortized Generation of Sequential Algorithmic Recourses for Black-box Models"

45 / 45 papers shown

Title
Learning Actionable Counterfactual Explanations in Large State Spaces Keziah Naggita Matthew R. Walter Avrim Blum OffRL 40 0 0 25 Apr 2024
Navigating Explanatory Multiverse Through Counterfactual Path Geometry Kacper Sokol E. Small Yueqing Xuan 47 5 0 05 Jun 2023
Consequence-aware Sequential Counterfactual Generation Philip Naumann Eirini Ntoutsi OffRL 40 25 0 12 Apr 2021
Counterfactuals and Causability in Explainable Artificial Intelligence: Theory, Algorithms, and Applications Yu-Liang Chou Catarina Moreira P. Bruza Chun Ouyang Joaquim A. Jorge CML 52 177 0 07 Mar 2021
Directive Explanations for Actionable Explainability in Machine Learning Applications Ronal Singh Paul Dourish Piers Howe Tim Miller L. Sonenberg Eduardo Velloso F. Vetere 16 33 0 03 Feb 2021
Expanding Explainability: Towards Social Transparency in AI systems Upol Ehsan Q. V. Liao Michael J. Muller Mark O. Riedl Justin D. Weisz 47 398 0 12 Jan 2021
A survey of algorithmic recourse: definitions, formulations, solutions, and prospects Amir-Hossein Karimi Gilles Barthe Bernhard Schölkopf Isabel Valera FaML 31 172 0 08 Oct 2020
Algorithmic recourse under imperfect causal knowledge: a probabilistic approach Amir-Hossein Karimi Julius von Kügelgen Bernhard Schölkopf Isabel Valera CML 77 179 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 42 146 0 26 May 2020
Multi-Objective Counterfactual Explanations Susanne Dandl Christoph Molnar Martin Binder B. Bischl 43 252 0 23 Apr 2020
Algorithmic Recourse: from Counterfactual Explanations to Interventions Amir-Hossein Karimi Bernhard Schölkopf Isabel Valera CML 29 339 0 14 Feb 2020
Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers Divyat Mahajan Chenhao Tan Amit Sharma OOD CML 73 206 0 06 Dec 2019
Learning Model-Agnostic Counterfactual Explanations for Tabular Data Martin Pawelczyk Johannes Haug Klaus Broelemann Gjergji Kasneci OOD CML 48 203 0 21 Oct 2019
Synthesizing Action Sequences for Modifying Model Decisions Goutham Ramakrishnan Yun Chan Lee Aws Albarghouthi 76 33 0 30 Sep 2019
FACE: Feasible and Actionable Counterfactual Explanations Rafael Poyiadzi Kacper Sokol Raúl Santos-Rodríguez T. D. Bie Peter A. Flach 52 368 0 20 Sep 2019
Measurable Counterfactual Local Explanations for Any Classifier Adam White Artur Garcez FAtt 20 99 0 08 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 32 186 0 22 Jul 2019
A Survey on Explainable Artificial Intelligence (XAI): Towards Medical XAI Erico Tjoa Cuntai Guan XAI 65 1,427 0 17 Jul 2019
Interpretable Counterfactual Explanations Guided by Prototypes A. V. Looveren Janis Klaise FAtt 36 380 0 03 Jul 2019
Generating Counterfactual and Contrastive Explanations using SHAP Shubham Rathi 35 56 0 21 Jun 2019
Model Agnostic Contrastive Explanations for Structured Data Amit Dhurandhar Tejaswini Pedapati Avinash Balakrishnan Pin-Yu Chen Karthikeyan Shanmugam Ruchi Puri FAtt 46 82 0 31 May 2019
Model-Agnostic Counterfactual Explanations for Consequential Decisions Amir-Hossein Karimi Gilles Barthe Borja Balle Isabel Valera 46 318 0 27 May 2019
CERTIFAI: Counterfactual Explanations for Robustness, Transparency, Interpretability, and Fairness of Artificial Intelligence models Shubham Sharma Jette Henderson Joydeep Ghosh 19 87 0 20 May 2019
Explaining Machine Learning Classifiers through Diverse Counterfactual Explanations R. Mothilal Amit Sharma Chenhao Tan CML 91 1,005 0 19 May 2019
Efficient Search for Diverse Coherent Explanations Chris Russell 38 236 0 02 Jan 2019
Improving fairness in machine learning systems: What do industry practitioners need? Kenneth Holstein Jennifer Wortman Vaughan Hal Daumé Miroslav Dudík Hanna M. Wallach FaML HAI 228 747 0 13 Dec 2018
Interpretable Credit Application Predictions With Counterfactual Explanations Rory Mc Grath Luca Costabello Chan Le Van Paul Sweeney F. Kamiab Zhao Shen Freddy Lecue FAtt 25 109 0 13 Nov 2018
Actionable Recourse in Linear Classification Berk Ustun Alexander Spangher Yang Liu FaML 77 545 0 18 Sep 2018
Local Rule-Based Explanations of Black Box Decision Systems Riccardo Guidotti A. Monreale Salvatore Ruggieri D. Pedreschi Franco Turini F. Giannotti 80 436 0 28 May 2018
Manipulating and Measuring Model Interpretability Forough Poursabzi-Sangdeh D. Goldstein Jake M. Hofman Jennifer Wortman Vaughan Hanna M. Wallach 48 693 0 21 Feb 2018
Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives Amit Dhurandhar Pin-Yu Chen Ronny Luss Chun-Chen Tu Pai-Shun Ting Karthikeyan Shanmugam Payel Das FAtt 69 587 0 21 Feb 2018
A Survey Of Methods For Explaining Black Box Models Riccardo Guidotti A. Monreale Salvatore Ruggieri Franco Turini D. Pedreschi F. Giannotti XAI 58 3,922 0 06 Feb 2018
Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR Sandra Wachter Brent Mittelstadt Chris Russell MLAU 27 2,332 0 01 Nov 2017
Proximal Policy Optimization Algorithms John Schulman Filip Wolski Prafulla Dhariwal Alec Radford Oleg Klimov OffRL 179 18,685 0 20 Jul 2017
Explanation in Artificial Intelligence: Insights from the Social Sciences Tim Miller XAI 195 4,229 0 22 Jun 2017
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization Ramprasaath R. Selvaraju Michael Cogswell Abhishek Das Ramakrishna Vedantam Devi Parikh Dhruv Batra FAtt 132 19,725 0 07 Oct 2016
Generalized Inverse Classification Michael T. Lash Qihang Lin W. Street Jennifer G. Robinson Jeffrey W. Ohlmann 26 60 0 05 Oct 2016
A Model Explanation System: Latest Updates and Extensions Ryan Turner FAtt 18 15 0 30 Jun 2016
OpenAI Gym Greg Brockman Vicki Cheung Ludwig Pettersson Jonas Schneider John Schulman Jie Tang Wojciech Zaremba OffRL ODL 143 5,048 0 05 Jun 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 100 16,765 0 16 Feb 2016
Asynchronous Methods for Deep Reinforcement Learning Volodymyr Mnih Adria Puigdomenech Badia M. Berk Mirza Alex Graves Timothy Lillicrap Tim Harley David Silver Koray Kavukcuoglu 134 8,805 0 04 Feb 2016
Learning Deep Features for Discriminative Localization Bolei Zhou A. Khosla Àgata Lapedriza A. Oliva Antonio Torralba SSL SSeg FAtt 76 9,266 0 14 Dec 2015
High-Dimensional Continuous Control Using Generalized Advantage Estimation John Schulman Philipp Moritz Sergey Levine Michael I. Jordan Pieter Abbeel OffRL 20 3,368 0 08 Jun 2015
Interpreting Tree Ensembles with inTrees Houtao Deng 49 241 0 23 Aug 2014
The Feature Importance Ranking Measure A. Zien Nicole Krämer Soeren Sonnenburg Gunnar Rätsch FAtt 56 147 0 23 Jun 2009