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Local Rule-Based Explanations of Black Box Decision Systems

Local Rule-Based Explanations of Black Box Decision Systems

28 May 2018
Riccardo Guidotti
A. Monreale
Salvatore Ruggieri
D. Pedreschi
Franco Turini
F. Giannotti
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Papers citing "Local Rule-Based Explanations of Black Box Decision Systems"

14 / 14 papers shown
Title
Graph Counterfactual Explainable AI via Latent Space Traversal
Graph Counterfactual Explainable AI via Latent Space Traversal
Andreas Abildtrup Hansen
Paraskevas Pegios
Anna Calissano
Aasa Feragen
OOD
BDL
AAML
92
0
0
15 Jan 2025
Explaining the Behavior of Black-Box Prediction Algorithms with Causal Learning
Explaining the Behavior of Black-Box Prediction Algorithms with Causal Learning
Numair Sani
Daniel Malinsky
I. Shpitser
CML
95
16
0
10 Jan 2025
BELLA: Black box model Explanations by Local Linear Approximations
BELLA: Black box model Explanations by Local Linear Approximations
N. Radulovic
Albert Bifet
Fabian M. Suchanek
FAtt
81
1
0
18 May 2023
Rule Generation for Classification: Scalability, Interpretability, and Fairness
Rule Generation for Classification: Scalability, Interpretability, and Fairness
Tabea E. Rober
Adia C. Lumadjeng
M. Akyuz
cS. .Ilker Birbil
80
2
0
21 Apr 2021
A Survey Of Methods For Explaining Black Box Models
A Survey Of Methods For Explaining Black Box Models
Riccardo Guidotti
A. Monreale
Salvatore Ruggieri
Franco Turini
D. Pedreschi
F. Giannotti
XAI
81
3,922
0
06 Feb 2018
Counterfactual Explanations without Opening the Black Box: Automated
  Decisions and the GDPR
Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR
Sandra Wachter
Brent Mittelstadt
Chris Russell
MLAU
70
2,332
0
01 Nov 2017
Fairness in Criminal Justice Risk Assessments: The State of the Art
Fairness in Criminal Justice Risk Assessments: The State of the Art
R. Berk
Hoda Heidari
S. Jabbari
Michael Kearns
Aaron Roth
40
990
0
27 Mar 2017
Towards A Rigorous Science of Interpretable Machine Learning
Towards A Rigorous Science of Interpretable Machine Learning
Finale Doshi-Velez
Been Kim
XAI
FaML
343
3,742
0
28 Feb 2017
Programs as Black-Box Explanations
Programs as Black-Box Explanations
Sameer Singh
Marco Tulio Ribeiro
Carlos Guestrin
FAtt
38
54
0
22 Nov 2016
Making Tree Ensembles Interpretable
Making Tree Ensembles Interpretable
Satoshi Hara
K. Hayashi
45
71
0
17 Jun 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
Marco Tulio Ribeiro
Sameer Singh
Carlos Guestrin
FAtt
FaML
519
16,765
0
16 Feb 2016
Learning Deep Features for Discriminative Localization
Learning Deep Features for Discriminative Localization
Bolei Zhou
A. Khosla
Àgata Lapedriza
A. Oliva
Antonio Torralba
SSL
SSeg
FAtt
157
9,266
0
14 Dec 2015
Show, Attend and Tell: Neural Image Caption Generation with Visual
  Attention
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
Ke Xu
Jimmy Ba
Ryan Kiros
Kyunghyun Cho
Aaron Courville
Ruslan Salakhutdinov
R. Zemel
Yoshua Bengio
DiffM
279
10,034
0
10 Feb 2015
Falling Rule Lists
Falling Rule Lists
Fulton Wang
Cynthia Rudin
36
258
0
21 Nov 2014
1