Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis

18 June 2021

Himabindu Lakkaraju

Papers citing "Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis"

37 / 37 papers shown

Title
Learning-Augmented Robust Algorithmic Recourse Kshitij Kayastha Vasilis Gkatzelis Shahin Jabbari 34 0 0 02 Oct 2024
CF-OPT: Counterfactual Explanations for Structured Prediction Germain Vivier--Ardisson Alexandre Forel Axel Parmentier Thibaut Vidal OffRL CML BDL 35 1 0 28 May 2024
Model-Based Counterfactual Explanations Incorporating Feature Space Attributes for Tabular Data Yuta Sumiya Hayaru Shouno AAML OOD 30 0 0 20 Apr 2024
Utilizing Adversarial Examples for Bias Mitigation and Accuracy Enhancement Pushkar Shukla Dhruv Srikanth Lee Cohen Matthew A. Turk AAML 38 0 0 18 Apr 2024
Do Counterfactual Examples Complicate Adversarial Training? Eric C. Yeats Cameron Darwin Eduardo Ortega Frank Liu Hai Li DiffM 37 0 0 16 Apr 2024
Towards Non-Adversarial Algorithmic Recourse Tobias Leemann Martin Pawelczyk Bardh Prenkaj Gjergji Kasneci AAML 28 1 0 15 Mar 2024
Cost-Adaptive Recourse Recommendation by Adaptive Preference Elicitation Duy Nguyen Bao Nguyen Viet Anh Nguyen 18 0 0 23 Feb 2024
Robust Counterfactual Explanations in Machine Learning: A Survey Junqi Jiang Francesco Leofante Antonio Rago Francesca Toni OffRL CML 28 10 0 02 Feb 2024
ABIGX: A Unified Framework for eXplainable Fault Detection and Classification Yue Zhuo Jinchuan Qian Zhihuan Song Zhiqiang Ge 14 1 0 09 Nov 2023
Faithful and Robust Local Interpretability for Textual Predictions Gianluigi Lopardo F. Precioso Damien Garreau OOD 26 4 0 30 Oct 2023
Adversarial Machine Learning for Social Good: Reframing the Adversary as an Ally Shawqi Al-Maliki Adnan Qayyum Hassan Ali M. Abdallah Junaid Qadir D. Hoang Dusit Niyato Ala I. Al-Fuqaha AAML 26 3 0 05 Oct 2023
On the Trade-offs between Adversarial Robustness and Actionable Explanations Satyapriya Krishna Chirag Agarwal Himabindu Lakkaraju AAML 36 0 0 28 Sep 2023
T-COL: Generating Counterfactual Explanations for General User Preferences on Variable Machine Learning Systems Yiming Li Daling Wang Wenfang Wu Shi Feng Yifei Zhang CML 40 1 0 28 Sep 2023
Adaptive Adversarial Training Does Not Increase Recourse Costs Ian Hardy Jayanth Yetukuri Yang Liu AAML 11 1 0 05 Sep 2023
Towards User Guided Actionable Recourse Jayanth Yetukuri Ian Hardy Yang Liu 13 2 0 05 Sep 2023
On Minimizing the Impact of Dataset Shifts on Actionable Explanations Anna P. Meyer Dan Ley Suraj Srinivas Himabindu Lakkaraju FAtt 34 6 0 11 Jun 2023
The Risks of Recourse in Binary Classification H. Fokkema Damien Garreau T. Erven FaML 16 4 0 01 Jun 2023
Unveiling the Potential of Counterfactuals Explanations in Employability Raphael Mazzine Barbosa de Oliveira S. Goethals Dieter Brughmans David Martens 19 2 0 17 May 2023
Algorithmic Recourse with Missing Values Kentaro Kanamori Takuya Takagi Ken Kobayashi Yuichi Ike 28 2 0 28 Apr 2023
Adversarial Counterfactual Visual Explanations Guillaume Jeanneret Loïc Simon F. Jurie DiffM 41 27 0 17 Mar 2023
Towards Bridging the Gaps between the Right to Explanation and the Right to be Forgotten Satyapriya Krishna Jiaqi Ma Himabindu Lakkaraju 24 13 0 08 Feb 2023
Robustness Implies Fairness in Causal Algorithmic Recourse A. Ehyaei Amir-Hossein Karimi Bernhard Schölkopf S. Maghsudi FaML 28 12 0 07 Feb 2023
On the Privacy Risks of Algorithmic Recourse Martin Pawelczyk Himabindu Lakkaraju Seth Neel 19 31 0 10 Nov 2022
Decomposing Counterfactual Explanations for Consequential Decision Making Martin Pawelczyk Lea Tiyavorabun Gjergji Kasneci CML 14 1 0 03 Nov 2022
A.I. Robustness: a Human-Centered Perspective on Technological Challenges and Opportunities Andrea Tocchetti Lorenzo Corti Agathe Balayn Mireia Yurrita Philip Lippmann Marco Brambilla Jie-jin Yang 19 10 0 17 Oct 2022
Formalising the Robustness of Counterfactual Explanations for Neural Networks Junqi Jiang Francesco Leofante Antonio Rago Francesca Toni AAML 15 26 0 31 Aug 2022
On the Trade-Off between Actionable Explanations and the Right to be Forgotten Martin Pawelczyk Tobias Leemann Asia J. Biega Gjergji Kasneci FaML MU 24 23 0 30 Aug 2022
The Manifold Hypothesis for Gradient-Based Explanations Sebastian Bordt Uddeshya Upadhyay Zeynep Akata U. V. Luxburg FAtt AAML 18 12 0 15 Jun 2022
Don't Explain Noise: Robust Counterfactuals for Randomized Ensembles Alexandre Forel Axel Parmentier Thibaut Vidal 22 1 0 27 May 2022
Diffusion Models for Counterfactual Explanations Guillaume Jeanneret Loïc Simon F. Jurie DiffM 32 55 0 29 Mar 2022
Probabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse Martin Pawelczyk Teresa Datta Johannes van-den-Heuvel Gjergji Kasneci Himabindu Lakkaraju 19 38 0 13 Mar 2022
On the Robustness of Sparse Counterfactual Explanations to Adverse Perturbations M. Virgolin Saverio Fracaros CML 26 36 0 22 Jan 2022
On the Adversarial Robustness of Causal Algorithmic Recourse Ricardo Dominguez-Olmedo Amir-Hossein Karimi Bernhard Schölkopf 46 63 0 21 Dec 2021
Estimating Categorical Counterfactuals via Deep Twin Networks Athanasios Vlontzos Bernhard Kainz Ciarán M. Gilligan-Lee OOD CML BDL 26 16 0 04 Sep 2021
Adversarial Attacks for Tabular Data: Application to Fraud Detection and Imbalanced Data F. Cartella Orlando Anunciação Yuki Funabiki D. Yamaguchi Toru Akishita Olivier Elshocht AAML 61 71 0 20 Jan 2021
Counterfactual Explanations and Algorithmic Recourses for Machine Learning: A Review Sahil Verma Varich Boonsanong Minh Hoang Keegan E. Hines John P. Dickerson Chirag Shah CML 24 162 0 20 Oct 2020
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 284 5,835 0 08 Jul 2016