Explanations for Monotonic Classifiers

1 June 2021

Papers citing "Explanations for Monotonic Classifiers"

24 / 24 papers shown

Title
Ranking Counterfactual Explanations Suryani Lim H. Prade G. Richard CML 68 0 0 20 Mar 2025
Hard to Explain: On the Computational Hardness of In-Distribution Model Interpretation Guy Amir Shahaf Bassan Guy Katz 44 2 0 07 Aug 2024
Local vs. Global Interpretability: A Computational Complexity Perspective Shahaf Bassan Guy Amir Guy Katz 43 6 0 05 Jun 2024
Model Reconstruction Using Counterfactual Explanations: Mitigating the Decision Boundary Shift Pasan Dissanayake Sanghamitra Dutta 51 1 0 08 May 2024
Anytime Approximate Formal Feature Attribution Jinqiang Yu Graham Farr Alexey Ignatiev Peter J. Stuckey 30 2 0 12 Dec 2023
Axiomatic Aggregations of Abductive Explanations Gagan Biradar Yacine Izza Elita Lobo Vignesh Viswanathan Yair Zick FAtt 11 4 0 29 Sep 2023
On Formal Feature Attribution and Its Approximation Jinqiang Yu Alexey Ignatiev Peter J. Stuckey 27 8 0 07 Jul 2023
Disproving XAI Myths with Formal Methods -- Initial Results Sasha Rubin 35 8 0 13 May 2023
A New Class of Explanations for Classifiers with Non-Binary Features Chunxi Ji Adnan Darwiche FAtt 26 3 0 28 Apr 2023
Finding Minimum-Cost Explanations for Predictions made by Tree Ensembles John Törnblom Emil Karlsson Simin Nadjm-Tehrani FAtt 51 0 0 16 Mar 2023
The Inadequacy of Shapley Values for Explainability Xuanxiang Huang Sasha Rubin FAtt 26 41 0 16 Feb 2023
On the Complexity of Enumerating Prime Implicants from Decision-DNNF Circuits Alexis de Colnet Pierre Marquis 18 9 0 30 Jan 2023
Some recent advances in reasoning based on analogical proportions Myriam Bounhas H. Prade G. Richard 9 1 0 22 Dec 2022
On Computing Probabilistic Abductive Explanations Yacine Izza Xuanxiang Huang Alexey Ignatiev Nina Narodytska Martin C. Cooper Sasha Rubin FAtt XAI 8 17 0 12 Dec 2022
Feature Necessity & Relevancy in ML Classifier Explanations Xuanxiang Huang Martin C. Cooper António Morgado Jordi Planes Sasha Rubin FAtt 32 18 0 27 Oct 2022
Logic-Based Explainability in Machine Learning Sasha Rubin LRM XAI 47 39 0 24 Oct 2022
On Computing Relevant Features for Explaining NBCs Yacine Izza Sasha Rubin 33 5 0 11 Jul 2022
On Computing Probabilistic Explanations for Decision Trees Marcelo Arenas Pablo Barceló M. Romero Bernardo Subercaseaux FAtt 37 38 0 30 Jun 2022
Eliminating The Impossible, Whatever Remains Must Be True Jinqiang Yu Alexey Ignatiev Peter J. Stuckey Nina Narodytska Sasha Rubin 19 23 0 20 Jun 2022
On Tackling Explanation Redundancy in Decision Trees Yacine Izza Alexey Ignatiev Sasha Rubin FAtt 48 58 0 20 May 2022
Cardinality-Minimal Explanations for Monotonic Neural Networks Ouns El Harzli Bernardo Cuenca Grau Ian Horrocks FAtt 38 5 0 19 May 2022
Defining and Quantifying the Emergence of Sparse Concepts in DNNs J. Ren Mingjie Li Qirui Chen Huiqi Deng Quanshi Zhang 18 31 0 11 Nov 2021
On Efficiently Explaining Graph-Based Classifiers Xuanxiang Huang Yacine Izza Alexey Ignatiev Sasha Rubin FAtt 34 37 0 02 Jun 2021
On Explaining Random Forests with SAT Yacine Izza Sasha Rubin FAtt 14 72 0 21 May 2021