Logic-Based Explainability in Machine Learning

24 October 2022

Papers citing "Logic-Based Explainability in Machine Learning"

33 / 33 papers shown

Title
Feature Relevancy, Necessity and Usefulness: Complexity and Algorithms Tomás Capdevielle Santiago Cifuentes FAtt 35 0 0 06 May 2025
On the Complexity of Global Necessary Reasons to Explain Classification M. Calautti Enrico Malizia Cristian Molinaro FAtt 63 0 0 12 Jan 2025
The Sets of Power Joao Marques-Silva Carlos Mencía Raúl Mencía 21 0 0 10 Oct 2024
Abductive and Contrastive Explanations for Scoring Rules in Voting Clément Contet Umberto Grandi Jérome Mengin FAtt 32 0 0 23 Aug 2024
Query languages for neural networks Martin Grohe Christoph Standke Juno Steegmans Jan Van den Bussche NAI 27 1 0 19 Aug 2024
Explaining Decisions in ML Models: a Parameterized Complexity Analysis S. Ordyniak Giacomo Paesani Mateusz Rychlicki Stefan Szeider 16 1 0 22 Jul 2024
Local vs. Global Interpretability: A Computational Complexity Perspective Shahaf Bassan Guy Amir Guy Katz 37 6 0 05 Jun 2024
Logic-Based Explainability: Past, Present & Future Joao Marques-Silva 26 2 0 04 Jun 2024
From SHAP Scores to Feature Importance Scores Olivier Letoffe Xuanxiang Huang Nicholas M. Asher Sasha Rubin FAtt 41 6 0 20 May 2024
Explainable AI (XAI) in Image Segmentation in Medicine, Industry, and Beyond: A Survey Rokas Gipiškis Chun-Wei Tsai Olga Kurasova 61 5 0 02 May 2024
A Uniform Language to Explain Decision Trees Marcelo Arenas Pablo Barceló Diego Bustamante Jose Caraball Bernardo Subercaseaux 11 0 0 18 Oct 2023
Refutation of Shapley Values for XAI -- Additional Evidence Xuanxiang Huang Sasha Rubin AAML 19 4 0 30 Sep 2023
A Refutation of Shapley Values for Explainability Xuanxiang Huang Sasha Rubin FAtt 13 3 0 06 Sep 2023
Explainable Answer-set Programming Tobias Geibinger LRM 17 1 0 30 Aug 2023
On Formal Feature Attribution and Its Approximation Jinqiang Yu Alexey Ignatiev Peter J. Stuckey 20 8 0 07 Jul 2023
Explainability is NOT a Game Sasha Rubin Xuanxiang Huang 16 17 0 27 Jun 2023
Disproving XAI Myths with Formal Methods -- Initial Results Sasha Rubin 35 8 0 13 May 2023
Attribution-Scores and Causal Counterfactuals as Explanations in Artificial Intelligence Leopoldo Bertossi XAI CML 28 5 0 06 Mar 2023
The Inadequacy of Shapley Values for Explainability Xuanxiang Huang Sasha Rubin FAtt 26 41 0 16 Feb 2023
COMET: Neural Cost Model Explanation Framework Isha Chaudhary Alex Renda Charith Mendis Gagandeep Singh 21 2 0 14 Feb 2023
A Scalable, Interpretable, Verifiable & Differentiable Logic Gate Convolutional Neural Network Architecture From Truth Tables Adrien Benamira Tristan Guérand Thomas Peyrin Trevor Yap Bryan Hooi 37 1 0 18 Aug 2022
On Computing Relevant Features for Explaining NBCs Yacine Izza Sasha Rubin 28 5 0 11 Jul 2022
On Tackling Explanation Redundancy in Decision Trees Yacine Izza Alexey Ignatiev Sasha Rubin FAtt 48 58 0 20 May 2022
Provably Precise, Succinct and Efficient Explanations for Decision Trees Yacine Izza Alexey Ignatiev Nina Narodytska Martin C. Cooper Sasha Rubin FAtt 32 7 0 19 May 2022
The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective Satyapriya Krishna Tessa Han Alex Gu Steven Wu S. Jabbari Himabindu Lakkaraju 177 186 0 03 Feb 2022
Efficiently Explaining CSPs with Unsatisfiable Subset Optimization Emilio Gamba B. Bogaerts Tias Guns LRM 34 6 0 25 May 2021
On the Complexity of SHAP-Score-Based Explanations: Tractability via Knowledge Compilation and Non-Approximability Results Marcelo Arenas Pablo Barceló Leopoldo Bertossi Mikaël Monet FAtt 14 35 0 16 Apr 2021
An Efficient Diagnosis Algorithm for Inconsistent Constraint Sets Alexander Felfernig Monika Schubert Christoph Zehentner 44 190 0 17 Feb 2021
Model Interpretability through the Lens of Computational Complexity Pablo Barceló Mikaël Monet Jorge A. Pérez Bernardo Subercaseaux 121 94 0 23 Oct 2020
Bridging the Gap: Providing Post-Hoc Symbolic Explanations for Sequential Decision-Making Problems with Inscrutable Representations S. Sreedharan Utkarsh Soni Mudit Verma Siddharth Srivastava S. Kambhampati 73 30 0 04 Feb 2020
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 234 2,238 0 24 Jun 2017
Learning Certifiably Optimal Rule Lists for Categorical Data E. Angelino Nicholas Larus-Stone Daniel Alabi Margo Seltzer Cynthia Rudin 51 195 0 06 Apr 2017
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 231 1,837 0 03 Feb 2017