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Logic for Explainable AI

Logic for Explainable AI

9 May 2023
Adnan Darwiche
ArXivPDFHTML

Papers citing "Logic for Explainable AI"

8 / 8 papers shown
Title
On the Complexity of Global Necessary Reasons to Explain Classification
On the Complexity of Global Necessary Reasons to Explain Classification
M. Calautti
Enrico Malizia
Cristian Molinaro
FAtt
63
0
0
12 Jan 2025
When is the Computation of a Feature Attribution Method Tractable?
P. Barceló
R. Cominetti
M. Morgado
TDI
FAtt
98
0
0
04 Jan 2025
Local vs. Global Interpretability: A Computational Complexity
  Perspective
Local vs. Global Interpretability: A Computational Complexity Perspective
Shahaf Bassan
Guy Amir
Guy Katz
35
6
0
05 Jun 2024
The Pros and Cons of Adversarial Robustness
The Pros and Cons of Adversarial Robustness
Yacine Izza
João Marques-Silva
AAML
25
1
0
18 Dec 2023
A New Class of Explanations for Classifiers with Non-Binary Features
A New Class of Explanations for Classifiers with Non-Binary Features
Chunxi Ji
Adnan Darwiche
FAtt
24
2
0
28 Apr 2023
Computing Abductive Explanations for Boosted Trees
Computing Abductive Explanations for Boosted Trees
Gilles Audemard
Jean-Marie Lagniez
Pierre Marquis
N. Szczepanski
24
12
0
16 Sep 2022
On Tackling Explanation Redundancy in Decision Trees
On Tackling Explanation Redundancy in Decision Trees
Yacine Izza
Alexey Ignatiev
João Marques-Silva
FAtt
48
57
0
20 May 2022
Model Interpretability through the Lens of Computational Complexity
Model Interpretability through the Lens of Computational Complexity
Pablo Barceló
Mikaël Monet
Jorge A. Pérez
Bernardo Subercaseaux
114
94
0
23 Oct 2020
1