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2010.04050
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A survey of algorithmic recourse: definitions, formulations, solutions, and prospects
8 October 2020
Amir-Hossein Karimi
Gilles Barthe
Bernhard Schölkopf
Isabel Valera
FaML
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Papers citing
"A survey of algorithmic recourse: definitions, formulations, solutions, and prospects"
45 / 95 papers shown
Title
MCCE: Monte Carlo sampling of realistic counterfactual explanations
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Solving the Class Imbalance Problem Using a Counterfactual Method for Data Augmentation
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Low-Cost Algorithmic Recourse for Users With Uncertain Cost Functions
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A Survey on the Robustness of Feature Importance and Counterfactual Explanations
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Jason Long
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224
66
0
30 Oct 2021
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497
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Multi-Agent Algorithmic Recourse
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224
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01 Oct 2021
Counterfactual Instances Explain Little
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Artur Garcez
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CounterNet: End-to-End Training of Prediction Aware Counterfactual Explanations
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T. Nguyen
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138
21
0
15 Sep 2021
CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms
Martin Pawelczyk
Sascha Bielawski
J. V. D. Heuvel
Tobias Richter
Gjergji Kasneci
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205
118
0
02 Aug 2021
A Framework and Benchmarking Study for Counterfactual Generating Methods on Tabular Data
Applied Sciences (AS), 2021
Raphael Mazzine
David Martens
180
35
0
09 Jul 2021
Counterfactual Explanations in Sequential Decision Making Under Uncertainty
Stratis Tsirtsis
A. De
Manuel Gomez Rodriguez
311
50
0
06 Jul 2021
Understanding Consumer Preferences for Explanations Generated by XAI Algorithms
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T. Vermeire
Olivier Toubia
David Martens
Theodoros Evgeniou
129
12
0
06 Jul 2021
Quantifying Availability and Discovery in Recommender Systems via Stochastic Reachability
International Conference on Machine Learning (ICML), 2021
Mihaela Curmei
Sarah Dean
Benjamin Recht
113
10
0
30 Jun 2021
Contrastive Counterfactual Visual Explanations With Overdetermination
Machine-mediated learning (ML), 2021
Adam White
K. Ngan
James Phelan
Saman Sadeghi Afgeh
Kevin Ryan
C. Reyes-Aldasoro
Artur Garcez
193
12
0
28 Jun 2021
Algorithmic Recourse in Partially and Fully Confounded Settings Through Bounding Counterfactual Effects
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N. Agarwal
Jakob Zeitler
Afsaneh Mastouri
Bernhard Schölkopf
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153
3
0
22 Jun 2021
Rational Shapley Values
Conference on Fairness, Accountability and Transparency (FAccT), 2021
David S. Watson
127
26
0
18 Jun 2021
Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Martin Pawelczyk
Chirag Agarwal
Shalmali Joshi
Sohini Upadhyay
Himabindu Lakkaraju
AAML
149
59
0
18 Jun 2021
Model-Based Counterfactual Synthesizer for Interpretation
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Sahan Suresh Alva
Jiahao Chen
X. Hu
98
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0
16 Jun 2021
Counterfactual Explanations for Machine Learning: Challenges Revisited
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John P Dickerson
Keegan E. Hines
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90
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0
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FairCanary: Rapid Continuous Explainable Fairness
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Avijit Ghosh
Aalok Shanbhag
Christo Wilson
234
23
0
13 Jun 2021
Optimal Counterfactual Explanations in Tree Ensembles
International Conference on Machine Learning (ICML), 2021
Axel Parmentier
Thibaut Vidal
172
60
0
11 Jun 2021
Amortized Generation of Sequential Algorithmic Recourses for Black-box Models
AAAI Conference on Artificial Intelligence (AAAI), 2021
Sahil Verma
Keegan E. Hines
John P. Dickerson
224
26
0
07 Jun 2021
Counterfactual Explanations Can Be Manipulated
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Dylan Slack
Sophie Hilgard
Himabindu Lakkaraju
Sameer Singh
156
155
0
04 Jun 2021
A Comprehensive Taxonomy for Explainable Artificial Intelligence: A Systematic Survey of Surveys on Methods and Concepts
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Gesina Schwalbe
Bettina Finzel
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337
258
0
15 May 2021
NICE: An Algorithm for Nearest Instance Counterfactual Explanations
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Dieter Brughmans
Pieter Leyman
David Martens
201
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0
15 Apr 2021
Consequence-aware Sequential Counterfactual Generation
Philip Naumann
Eirini Ntoutsi
OffRL
166
26
0
12 Apr 2021
Handling Climate Change Using Counterfactuals: Using Counterfactuals in Data Augmentation to Predict Crop Growth in an Uncertain Climate Future
International Conference on Case-Based Reasoning (ICCBR), 2021
M. Temraz
Eoin M. Kenny
E. Ruelle
L. Shalloo
Barry Smyth
Markt. Keane
100
7
0
08 Apr 2021
Local Explanations via Necessity and Sufficiency: Unifying Theory and Practice
Minds and Machines (Minds Mach.), 2021
David S. Watson
Limor Gultchin
Ankur Taly
Luciano Floridi
158
69
0
27 Mar 2021
Explaining Black-Box Algorithms Using Probabilistic Contrastive Counterfactuals
Sainyam Galhotra
Romila Pradhan
Babak Salimi
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214
117
0
22 Mar 2021
Counterfactuals and Causability in Explainable Artificial Intelligence: Theory, Algorithms, and Applications
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Yu-Liang Chou
Catarina Moreira
P. Bruza
Chun Ouyang
Joaquim A. Jorge
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315
213
0
07 Mar 2021
Strategic Classification Made Practical
International Conference on Machine Learning (ICML), 2021
Sagi Levanon
Nir Rosenfeld
206
66
0
02 Mar 2021
Towards Robust and Reliable Algorithmic Recourse
Neural Information Processing Systems (NeurIPS), 2021
Sohini Upadhyay
Shalmali Joshi
Himabindu Lakkaraju
191
121
0
26 Feb 2021
If Only We Had Better Counterfactual Explanations: Five Key Deficits to Rectify in the Evaluation of Counterfactual XAI Techniques
International Joint Conference on Artificial Intelligence (IJCAI), 2021
Mark T. Keane
Eoin M. Kenny
Eoin Delaney
Barry Smyth
CML
250
164
0
26 Feb 2021
Benchmarking and Survey of Explanation Methods for Black Box Models
Data mining and knowledge discovery (DMKD), 2021
F. Bodria
F. Giannotti
Riccardo Guidotti
Francesca Naretto
D. Pedreschi
S. Rinzivillo
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302
276
0
25 Feb 2021
Everything is Relative: Understanding Fairness with Optimal Transport
Kweku Kwegyir-Aggrey
Rebecca Santorella
Sarah M. Brown
OT
151
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CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Ana Lucic
Maartje ter Hoeve
Gabriele Tolomei
Maarten de Rijke
Fabrizio Silvestri
413
167
0
05 Feb 2021
Conditional Generative Models for Counterfactual Explanations
A. V. Looveren
Janis Klaise
G. Vacanti
Oliver Cobb
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125
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Interpretability and Explainability: A Machine Learning Zoo Mini-tour
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Julia E. Vogt
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305
132
0
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Linear Classifiers that Encourage Constructive Adaptation
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Jialu Wang
Yang Liu
288
18
0
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Explainable Machine Learning for Public Policy: Use Cases, Gaps, and Research Directions
Data & Policy (DP), 2020
Kasun Amarasinghe
Kit Rodolfa
Hemank Lamba
Rayid Ghani
ELM
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419
66
0
27 Oct 2020
On the Fairness of Causal Algorithmic Recourse
Julius von Kügelgen
Amir-Hossein Karimi
Umang Bhatt
Isabel Valera
Adrian Weller
Bernhard Schölkopf
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553
91
0
13 Oct 2020
Scaling Guarantees for Nearest Counterfactual Explanations
AAAI/ACM Conference on AI, Ethics, and Society (AIES), 2020
Kiarash Mohammadi
Amir-Hossein Karimi
Gilles Barthe
Isabel Valera
LRM
164
35
0
10 Oct 2020
The Intriguing Relation Between Counterfactual Explanations and Adversarial Examples
Minds and Machines (MM), 2020
Timo Freiesleben
GAN
444
69
0
11 Sep 2020
Algorithmic recourse under imperfect causal knowledge: a probabilistic approach
Neural Information Processing Systems (NeurIPS), 2020
Amir-Hossein Karimi
Julius von Kügelgen
Bernhard Schölkopf
Isabel Valera
CML
334
189
0
11 Jun 2020
PRINCE: Provider-side Interpretability with Counterfactual Explanations in Recommender Systems
Web Search and Data Mining (WSDM), 2019
Azin Ghazimatin
Oana Balalau
Rishiraj Saha Roy
Gerhard Weikum
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330
104
0
19 Nov 2019
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