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A survey of algorithmic recourse: definitions, formulations, solutions,
  and prospects
v1v2 (latest)

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

8 October 2020
Amir-Hossein Karimi
Gilles Barthe
Bernhard Schölkopf
Isabel Valera
    FaML
ArXiv (abs)PDFHTML

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
MCCE: Monte Carlo sampling of realistic counterfactual explanations
Annabelle Redelmeier
Martin Jullum
K. Aas
Anders Løland
BDL
148
11
0
18 Nov 2021
Solving the Class Imbalance Problem Using a Counterfactual Method for
  Data Augmentation
Solving the Class Imbalance Problem Using a Counterfactual Method for Data Augmentation
M. Temraz
Markt. Keane
151
55
0
05 Nov 2021
Low-Cost Algorithmic Recourse for Users With Uncertain Cost Functions
Low-Cost Algorithmic Recourse for Users With Uncertain Cost Functions
Prateek Yadav
Peter Hase
Joey Tianyi Zhou
198
12
0
01 Nov 2021
A Survey on the Robustness of Feature Importance and Counterfactual
  Explanations
A Survey on the Robustness of Feature Importance and Counterfactual Explanations
Saumitra Mishra
Sanghamitra Dutta
Jason Long
Daniele Magazzeni
AAML
224
66
0
30 Oct 2021
Deep Neural Networks and Tabular Data: A Survey
Deep Neural Networks and Tabular Data: A Survey
V. Borisov
Tobias Leemann
Kathrin Seßler
Johannes Haug
Martin Pawelczyk
Gjergji Kasneci
LMTD
497
922
0
05 Oct 2021
Multi-Agent Algorithmic Recourse
Multi-Agent Algorithmic Recourse
Andrew O'Brien
Edward J. Kim
224
4
0
01 Oct 2021
Counterfactual Instances Explain Little
Counterfactual Instances Explain Little
Adam White
Artur Garcez
CML
109
5
0
20 Sep 2021
CounterNet: End-to-End Training of Prediction Aware Counterfactual
  Explanations
CounterNet: End-to-End Training of Prediction Aware Counterfactual Explanations
Hangzhi Guo
T. Nguyen
A. Yadav
OffRL
138
21
0
15 Sep 2021
CARLA: A Python Library to Benchmark Algorithmic Recourse and
  Counterfactual Explanation Algorithms
CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms
Martin Pawelczyk
Sascha Bielawski
J. V. D. Heuvel
Tobias Richter
Gjergji Kasneci
CML
205
118
0
02 Aug 2021
A Framework and Benchmarking Study for Counterfactual Generating Methods
  on Tabular Data
A Framework and Benchmarking Study for Counterfactual Generating Methods on Tabular DataApplied Sciences (AS), 2021
Raphael Mazzine
David Martens
180
35
0
09 Jul 2021
Counterfactual Explanations in Sequential Decision Making Under
  Uncertainty
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
Understanding Consumer Preferences for Explanations Generated by XAI Algorithms
Yanou Ramon
T. Vermeire
Olivier Toubia
David Martens
Theodoros Evgeniou
129
12
0
06 Jul 2021
Quantifying Availability and Discovery in Recommender Systems via
  Stochastic Reachability
Quantifying Availability and Discovery in Recommender Systems via Stochastic ReachabilityInternational Conference on Machine Learning (ICML), 2021
Mihaela Curmei
Sarah Dean
Benjamin Recht
113
10
0
30 Jun 2021
Contrastive Counterfactual Visual Explanations With Overdetermination
Contrastive Counterfactual Visual Explanations With OverdeterminationMachine-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
Algorithmic Recourse in Partially and Fully Confounded Settings Through Bounding Counterfactual Effects
Julius von Kügelgen
N. Agarwal
Jakob Zeitler
Afsaneh Mastouri
Bernhard Schölkopf
CML
153
3
0
22 Jun 2021
Rational Shapley Values
Rational Shapley ValuesConference 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
Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical AnalysisInternational 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
Model-Based Counterfactual Synthesizer for Interpretation
Fan Yang
Sahan Suresh Alva
Jiahao Chen
X. Hu
98
34
0
16 Jun 2021
Counterfactual Explanations for Machine Learning: Challenges Revisited
Counterfactual Explanations for Machine Learning: Challenges Revisited
Sahil Verma
John P Dickerson
Keegan E. Hines
LRM
90
37
0
14 Jun 2021
FairCanary: Rapid Continuous Explainable Fairness
FairCanary: Rapid Continuous Explainable FairnessAAAI/ACM Conference on AI, Ethics, and Society (AIES), 2021
Avijit Ghosh
Aalok Shanbhag
Christo Wilson
234
23
0
13 Jun 2021
Optimal Counterfactual Explanations in Tree Ensembles
Optimal Counterfactual Explanations in Tree EnsemblesInternational 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
Amortized Generation of Sequential Algorithmic Recourses for Black-box ModelsAAAI 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
Counterfactual Explanations Can Be ManipulatedNeural Information Processing Systems (NeurIPS), 2021
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
A Comprehensive Taxonomy for Explainable Artificial Intelligence: A Systematic Survey of Surveys on Methods and ConceptsData mining and knowledge discovery (DMKD), 2021
Gesina Schwalbe
Bettina Finzel
XAI
337
258
0
15 May 2021
NICE: An Algorithm for Nearest Instance Counterfactual Explanations
NICE: An Algorithm for Nearest Instance Counterfactual ExplanationsData mining and knowledge discovery (DMKD), 2021
Dieter Brughmans
Pieter Leyman
David Martens
201
79
0
15 Apr 2021
Consequence-aware Sequential Counterfactual Generation
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
Handling Climate Change Using Counterfactuals: Using Counterfactuals in Data Augmentation to Predict Crop Growth in an Uncertain Climate FutureInternational 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
Local Explanations via Necessity and Sufficiency: Unifying Theory and PracticeMinds 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
Explaining Black-Box Algorithms Using Probabilistic Contrastive Counterfactuals
Sainyam Galhotra
Romila Pradhan
Babak Salimi
CML
214
117
0
22 Mar 2021
Counterfactuals and Causability in Explainable Artificial Intelligence:
  Theory, Algorithms, and Applications
Counterfactuals and Causability in Explainable Artificial Intelligence: Theory, Algorithms, and ApplicationsInformation Fusion (Inf. Fusion), 2021
Yu-Liang Chou
Catarina Moreira
P. Bruza
Chun Ouyang
Joaquim A. Jorge
CML
315
213
0
07 Mar 2021
Strategic Classification Made Practical
Strategic Classification Made PracticalInternational Conference on Machine Learning (ICML), 2021
Sagi Levanon
Nir Rosenfeld
206
66
0
02 Mar 2021
Towards Robust and Reliable Algorithmic Recourse
Towards Robust and Reliable Algorithmic RecourseNeural 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
If Only We Had Better Counterfactual Explanations: Five Key Deficits to Rectify in the Evaluation of Counterfactual XAI TechniquesInternational 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
Benchmarking and Survey of Explanation Methods for Black Box ModelsData mining and knowledge discovery (DMKD), 2021
F. Bodria
F. Giannotti
Riccardo Guidotti
Francesca Naretto
D. Pedreschi
S. Rinzivillo
XAI
302
276
0
25 Feb 2021
Everything is Relative: Understanding Fairness with Optimal Transport
Everything is Relative: Understanding Fairness with Optimal Transport
Kweku Kwegyir-Aggrey
Rebecca Santorella
Sarah M. Brown
OT
151
5
0
20 Feb 2021
CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks
CF-GNNExplainer: Counterfactual Explanations for Graph Neural NetworksInternational 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
Conditional Generative Models for Counterfactual Explanations
A. V. Looveren
Janis Klaise
G. Vacanti
Oliver Cobb
CML
125
36
0
25 Jan 2021
Interpretability and Explainability: A Machine Learning Zoo Mini-tour
Interpretability and Explainability: A Machine Learning Zoo Mini-tour
Ricards Marcinkevics
Julia E. Vogt
XAI
305
132
0
03 Dec 2020
Linear Classifiers that Encourage Constructive Adaptation
Linear Classifiers that Encourage Constructive Adaptation
Yatong Chen
Jialu Wang
Yang Liu
288
18
0
31 Oct 2020
Explainable Machine Learning for Public Policy: Use Cases, Gaps, and
  Research Directions
Explainable Machine Learning for Public Policy: Use Cases, Gaps, and Research DirectionsData & Policy (DP), 2020
Kasun Amarasinghe
Kit Rodolfa
Hemank Lamba
Rayid Ghani
ELMXAI
419
66
0
27 Oct 2020
On the Fairness of Causal Algorithmic Recourse
On the Fairness of Causal Algorithmic Recourse
Julius von Kügelgen
Amir-Hossein Karimi
Umang Bhatt
Isabel Valera
Adrian Weller
Bernhard Schölkopf
FaML
553
91
0
13 Oct 2020
Scaling Guarantees for Nearest Counterfactual Explanations
Scaling Guarantees for Nearest Counterfactual ExplanationsAAAI/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
The Intriguing Relation Between Counterfactual Explanations and Adversarial ExamplesMinds and Machines (MM), 2020
Timo Freiesleben
GAN
444
69
0
11 Sep 2020
Algorithmic recourse under imperfect causal knowledge: a probabilistic
  approach
Algorithmic recourse under imperfect causal knowledge: a probabilistic approachNeural 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
PRINCE: Provider-side Interpretability with Counterfactual Explanations in Recommender SystemsWeb Search and Data Mining (WSDM), 2019
Azin Ghazimatin
Oana Balalau
Rishiraj Saha Roy
Gerhard Weikum
FAtt
330
104
0
19 Nov 2019
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