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On the Computational Intelligibility of Boolean Classifiers

On the Computational Intelligibility of Boolean Classifiers

13 April 2021
Gilles Audemard
S. Bellart
Louenas Bounia
F. Koriche
Jean-Marie Lagniez
Pierre Marquis
ArXivPDFHTML

Papers citing "On the Computational Intelligibility of Boolean Classifiers"

19 / 19 papers shown
Title
Interpretable DNFs
Interpretable DNFs
Martin C. Cooper
Imane Bousdira
Clément Carbonnel
FAtt
AI4CE
20
0
0
27 May 2025
Learning outside the Black-Box: The pursuit of interpretable models
Learning outside the Black-Box: The pursuit of interpretable models
Jonathan Crabbé
Yao Zhang
W. Zame
M. Schaar
26
24
0
17 Nov 2020
On Explaining Decision Trees
On Explaining Decision Trees
Yacine Izza
Alexey Ignatiev
Sasha Rubin
FAtt
60
88
0
21 Oct 2020
On the Tractability of SHAP Explanations
On the Tractability of SHAP Explanations
Guy Van den Broeck
A. Lykov
Maximilian Schleich
Dan Suciu
FAtt
TDI
55
269
0
18 Sep 2020
Explaining Naive Bayes and Other Linear Classifiers with Polynomial Time
  and Delay
Explaining Naive Bayes and Other Linear Classifiers with Polynomial Time and Delay
Sasha Rubin
Thomas Gerspacher
Martin C. Cooper
Alexey Ignatiev
Nina Narodytska
FAtt
49
62
0
13 Aug 2020
Efficient Exact Verification of Binarized Neural Networks
Efficient Exact Verification of Binarized Neural Networks
Kai Jia
Martin Rinard
AAML
MQ
21
59
0
07 May 2020
Model Agnostic Multilevel Explanations
Model Agnostic Multilevel Explanations
Karthikeyan N. Ramamurthy
B. Vinzamuri
Yunfeng Zhang
Amit Dhurandhar
63
42
0
12 Mar 2020
On The Reasons Behind Decisions
On The Reasons Behind Decisions
Adnan Darwiche
Auguste Hirth
FaML
49
147
0
21 Feb 2020
Robustness Verification of Tree-based Models
Robustness Verification of Tree-based Models
Hongge Chen
Huan Zhang
Si Si
Yang Li
Duane S. Boning
Cho-Jui Hsieh
AAML
49
77
0
10 Jun 2019
Significance Tests for Neural Networks
Significance Tests for Neural Networks
Enguerrand Horel
K. Giesecke
28
55
0
16 Feb 2019
Abduction-Based Explanations for Machine Learning Models
Abduction-Based Explanations for Machine Learning Models
Alexey Ignatiev
Nina Narodytska
Sasha Rubin
FAtt
57
224
0
26 Nov 2018
Model Agnostic Supervised Local Explanations
Model Agnostic Supervised Local Explanations
Gregory Plumb
Denali Molitor
Ameet Talwalkar
FAtt
LRM
MILM
92
197
0
09 Jul 2018
Logical Explanations for Deep Relational Machines Using Relevance
  Information
Logical Explanations for Deep Relational Machines Using Relevance Information
A. Srinivasan
Lovekesh Vig
Michael Bain
FAtt
22
15
0
02 Jul 2018
A Symbolic Approach to Explaining Bayesian Network Classifiers
A Symbolic Approach to Explaining Bayesian Network Classifiers
Andy Shih
Arthur Choi
Adnan Darwiche
FAtt
64
243
0
09 May 2018
Stability and Generalization of Learning Algorithms that Converge to
  Global Optima
Stability and Generalization of Learning Algorithms that Converge to Global Optima
Zachary B. Charles
Dimitris Papailiopoulos
MLT
40
162
0
23 Oct 2017
Verifying Properties of Binarized Deep Neural Networks
Verifying Properties of Binarized Deep Neural Networks
Nina Narodytska
S. Kasiviswanathan
L. Ryzhyk
Shmuel Sagiv
T. Walsh
AAML
64
217
0
19 Sep 2017
European Union regulations on algorithmic decision-making and a "right
  to explanation"
European Union regulations on algorithmic decision-making and a "right to explanation"
B. Goodman
Seth Flaxman
FaML
AILaw
63
1,897
0
28 Jun 2016
The Mythos of Model Interpretability
The Mythos of Model Interpretability
Zachary Chase Lipton
FaML
160
3,685
0
10 Jun 2016
A Knowledge Compilation Map
A Knowledge Compilation Map
Adnan Darwiche
Pierre Marquis
82
953
0
09 Jun 2011
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