Efficient Explanations With Relevant Sets

1 June 2021

Papers citing "Efficient Explanations With Relevant Sets"

20 / 20 papers shown

Title
On Guaranteed Optimal Robust Explanations for NLP Models Emanuele La Malfa A. Zbrzezny Rhiannon Michelmore Nicola Paoletti Marta Z. Kwiatkowska FAtt 29 47 0 08 May 2021
On the Computational Intelligibility of Boolean Classifiers Gilles Audemard S. Bellart Louenas Bounia F. Koriche Jean-Marie Lagniez Pierre Marquis 29 57 0 13 Apr 2021
Model Interpretability through the Lens of Computational Complexity Pablo Barceló Mikaël Monet Jorge A. Pérez Bernardo Subercaseaux 150 96 0 23 Oct 2020
On Explaining Decision Trees Yacine Izza Alexey Ignatiev Sasha Rubin FAtt 36 86 0 21 Oct 2020
On The Reasons Behind Decisions Adnan Darwiche Auguste Hirth FaML 25 145 0 21 Feb 2020
"How do I fool you?": Manipulating User Trust via Misleading Black Box Explanations Himabindu Lakkaraju Osbert Bastani 30 251 0 15 Nov 2019
Fooling LIME and SHAP: Adversarial Attacks on Post hoc Explanation Methods Dylan Slack Sophie Hilgard Emily Jia Sameer Singh Himabindu Lakkaraju FAtt AAML MLAU 37 809 0 06 Nov 2019
Can I Trust the Explainer? Verifying Post-hoc Explanatory Methods Oana-Maria Camburu Eleonora Giunchiglia Jakob N. Foerster Thomas Lukasiewicz Phil Blunsom FAtt AAML 34 61 0 04 Oct 2019
What to Expect of Classifiers? Reasoning about Logistic Regression with Missing Features Pasha Khosravi Yitao Liang YooJung Choi Guy Van den Broeck 19 44 0 05 Mar 2019
Abduction-Based Explanations for Machine Learning Models Alexey Ignatiev Nina Narodytska Sasha Rubin FAtt 27 223 0 26 Nov 2018
A Symbolic Approach to Explaining Bayesian Network Classifiers Andy Shih Arthur Choi Adnan Darwiche FAtt 44 241 0 09 May 2018
The Challenge of Crafting Intelligible Intelligence Daniel S. Weld Gagan Bansal 26 243 0 09 Mar 2018
A Survey Of Methods For Explaining Black Box Models Riccardo Guidotti A. Monreale Salvatore Ruggieri Franco Turini D. Pedreschi F. Giannotti XAI 58 3,922 0 06 Feb 2018
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 250 2,248 0 24 Jun 2017
Explanation in Artificial Intelligence: Insights from the Social Sciences Tim Miller XAI 195 4,229 0 22 Jun 2017
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 36 21,459 0 22 May 2017
PMLB: A Large Benchmark Suite for Machine Learning Evaluation and Comparison Randal S. Olson William La Cava Patryk Orzechowski Ryan J. Urbanowicz J. Moore 26 377 0 01 Mar 2017
The Mythos of Model Interpretability Zachary Chase Lipton FaML 37 3,672 0 10 Jun 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 100 16,765 0 16 Feb 2016
A Knowledge Compilation Map Adnan Darwiche Pierre Marquis 38 948 0 09 Jun 2011