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Interpretable Regional Descriptors: Hyperbox-Based Local Explanations

Interpretable Regional Descriptors: Hyperbox-Based Local Explanations

4 May 2023
Susanne Dandl
Giuseppe Casalicchio
Bernd Bischl
Ludwig Bothmann
ArXivPDFHTML

Papers citing "Interpretable Regional Descriptors: Hyperbox-Based Local Explanations"

7 / 7 papers shown
Title
Data Science Principles for Interpretable and Explainable AI
Data Science Principles for Interpretable and Explainable AI
Kris Sankaran
FaML
40
0
0
17 May 2024
Counterfactual and Semifactual Explanations in Abstract Argumentation:
  Formal Foundations, Complexity and Computation
Counterfactual and Semifactual Explanations in Abstract Argumentation: Formal Foundations, Complexity and Computation
Gianvincenzo Alfano
S. Greco
Francesco Parisi
I. Trubitsyna
24
1
0
07 May 2024
Guarantee Regions for Local Explanations
Guarantee Regions for Local Explanations
Marton Havasi
S. Parbhoo
Finale Doshi-Velez
FAtt
AAML
25
0
0
20 Feb 2024
Even-if Explanations: Formal Foundations, Priorities and Complexity
Even-if Explanations: Formal Foundations, Priorities and Complexity
Gianvincenzo Alfano
S. Greco
Domenico Mandaglio
Francesco Parisi
Reza Shahbazian
I. Trubitsyna
26
2
0
17 Jan 2024
What Makes a Good Explanation?: A Harmonized View of Properties of
  Explanations
What Makes a Good Explanation?: A Harmonized View of Properties of Explanations
Zixi Chen
Varshini Subhash
Marton Havasi
Weiwei Pan
Finale Doshi-Velez
XAI
FAtt
36
18
0
10 Nov 2022
Towards A Rigorous Science of Interpretable Machine Learning
Towards A Rigorous Science of Interpretable Machine Learning
Finale Doshi-Velez
Been Kim
XAI
FaML
257
3,690
0
28 Feb 2017
SMOTE: Synthetic Minority Over-sampling Technique
SMOTE: Synthetic Minority Over-sampling Technique
Nitesh V. Chawla
Kevin W. Bowyer
Lawrence Hall
W. Kegelmeyer
AI4TS
163
25,273
0
09 Jun 2011
1