Towards Robust and Reliable Algorithmic Recourse

26 February 2021

Himabindu Lakkaraju

Papers citing "Towards Robust and Reliable Algorithmic Recourse"

25 / 25 papers shown

Title
Axiomatic Explainer Globalness via Optimal Transport Davin Hill Josh Bone A. Masoomi Max Torop Jennifer Dy 145 1 0 13 Mar 2025
Understanding Fixed Predictions via Confined Regions Connor Lawless Tsui-Wei Weng Berk Ustun Madeleine Udell 70 0 0 22 Feb 2025
Feature Responsiveness Scores: Model-Agnostic Explanations for Recourse Seung Hyun Cheon Anneke Wernerfelt Sorelle A. Friedler Berk Ustun FaML FAtt 129 1 0 29 Oct 2024
HR-Bandit: Human-AI Collaborated Linear Recourse Bandit Junyu Cao Ruijiang Gao Esmaeil Keyvanshokooh 121 1 0 18 Oct 2024
What is different between these datasets? Varun Babbar Zhicheng Guo Cynthia Rudin 69 1 0 08 Mar 2024
BayLIME: Bayesian Local Interpretable Model-Agnostic Explanations Xingyu Zhao Wei Huang Xiaowei Huang Valentin Robu David Flynn FAtt 58 92 0 05 Dec 2020
Robust and Stable Black Box Explanations Himabindu Lakkaraju Nino Arsov Osbert Bastani AAML FAtt 46 84 0 12 Nov 2020
A survey of algorithmic recourse: definitions, formulations, solutions, and prospects Amir-Hossein Karimi Gilles Barthe Bernhard Schölkopf Isabel Valera FaML 50 172 0 08 Oct 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
Algorithmic Recourse: from Counterfactual Explanations to Interventions Amir-Hossein Karimi Bernhard Schölkopf Isabel Valera CML 44 340 0 14 Feb 2020
Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers Divyat Mahajan Chenhao Tan Amit Sharma OOD CML 85 206 0 06 Dec 2019
FACE: Feasible and Actionable Counterfactual Explanations Rafael Poyiadzi Kacper Sokol Raúl Santos-Rodríguez T. D. Bie Peter A. Flach 64 368 0 20 Sep 2019
Interpretable Counterfactual Explanations Guided by Prototypes A. V. Looveren Janis Klaise FAtt 47 380 0 03 Jul 2019
Model Agnostic Contrastive Explanations for Structured Data Amit Dhurandhar Tejaswini Pedapati Avinash Balakrishnan Pin-Yu Chen Karthikeyan Shanmugam Ruchi Puri FAtt 59 82 0 31 May 2019
Model-Agnostic Counterfactual Explanations for Consequential Decisions Amir-Hossein Karimi Gilles Barthe Borja Balle Isabel Valera 76 320 0 27 May 2019
Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift Stephan Rabanser Stephan Günnemann Zachary Chase Lipton 52 363 0 29 Oct 2018
Adversarial Attacks and Defences: A Survey Anirban Chakraborty Manaar Alam Vishal Dey Anupam Chattopadhyay Debdeep Mukhopadhyay AAML OOD 51 676 0 28 Sep 2018
Actionable Recourse in Linear Classification Berk Ustun Alexander Spangher Yang Liu FaML 84 545 0 18 Sep 2018
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples Anish Athalye Nicholas Carlini D. Wagner AAML 161 3,171 0 01 Feb 2018
Provable defenses against adversarial examples via the convex outer adversarial polytope Eric Wong J. Zico Kolter AAML 78 1,495 0 02 Nov 2017
Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR Sandra Wachter Brent Mittelstadt Chris Russell MLAU 81 2,332 0 01 Nov 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 229 11,962 0 19 Jun 2017
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 587 16,828 0 16 Feb 2016
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 176 18,922 0 20 Dec 2014