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Scaling Guarantees for Nearest Counterfactual Explanations

Scaling Guarantees for Nearest Counterfactual Explanations

10 October 2020
Kiarash Mohammadi
Amir-Hossein Karimi
Gilles Barthe
Isabel Valera
    LRM
ArXivPDFHTML

Papers citing "Scaling Guarantees for Nearest Counterfactual Explanations"

11 / 11 papers shown
Title
Generating Likely Counterfactuals Using Sum-Product Networks
Generating Likely Counterfactuals Using Sum-Product Networks
Jiri Nemecek
Tomás Pevný
Jakub Marecek
TPM
76
0
0
25 Jan 2024
Finding Optimal Diverse Feature Sets with Alternative Feature Selection
Finding Optimal Diverse Feature Sets with Alternative Feature Selection
Jakob Bach
29
1
0
21 Jul 2023
GAM Coach: Towards Interactive and User-centered Algorithmic Recourse
GAM Coach: Towards Interactive and User-centered Algorithmic Recourse
Zijie J. Wang
J. W. Vaughan
R. Caruana
Duen Horng Chau
HAI
41
21
0
27 Feb 2023
Understanding User Preferences in Explainable Artificial Intelligence: A
  Survey and a Mapping Function Proposal
Understanding User Preferences in Explainable Artificial Intelligence: A Survey and a Mapping Function Proposal
M. Hashemi
Ali Darejeh
Francisco Cruz
47
3
0
07 Feb 2023
Robust Explanation Constraints for Neural Networks
Robust Explanation Constraints for Neural Networks
Matthew Wicker
Juyeon Heo
Luca Costabello
Adrian Weller
FAtt
34
18
0
16 Dec 2022
Formalising the Robustness of Counterfactual Explanations for Neural
  Networks
Formalising the Robustness of Counterfactual Explanations for Neural Networks
Junqi Jiang
Francesco Leofante
Antonio Rago
Francesca Toni
AAML
29
27
0
31 Aug 2022
FETA: Fairness Enforced Verifying, Training, and Predicting Algorithms
  for Neural Networks
FETA: Fairness Enforced Verifying, Training, and Predicting Algorithms for Neural Networks
Kiarash Mohammadi
Aishwarya Sivaraman
G. Farnadi
27
5
0
01 Jun 2022
Counterfactual Explanations and Algorithmic Recourses for Machine
  Learning: A Review
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
26
164
0
20 Oct 2020
BRPO: Batch Residual Policy Optimization
BRPO: Batch Residual Policy Optimization
Kentaro Kanamori
Yinlam Chow
Takuya Takagi
Hiroki Arimura
Honglak Lee
Ken Kobayashi
Craig Boutilier
OffRL
141
46
0
08 Feb 2020
Towards A Rigorous Science of Interpretable Machine Learning
Towards A Rigorous Science of Interpretable Machine Learning
Finale Doshi-Velez
Been Kim
XAI
FaML
257
3,698
0
28 Feb 2017
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Guy Katz
Clark W. Barrett
D. Dill
Kyle D. Julian
Mykel Kochenderfer
AAML
251
1,842
0
03 Feb 2017
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