Computing Optimal Decision Sets with SAT

29 July 2020

Papers citing "Computing Optimal Decision Sets with SAT"

11 / 11 papers shown

Title
Three Modern Roles for Logic in AI Adnan Darwiche AI4CE 115 56 0 18 Apr 2020
MLIC: A MaxSAT-Based framework for learning interpretable classification rules Dmitry Malioutov Kuldeep S. Meel 50 44 0 05 Dec 2018
Boolean Decision Rules via Column Generation S. Dash Oktay Gunluk Dennis L. Wei 67 175 0 24 May 2018
A Symbolic Approach to Explaining Bayesian Network Classifiers Andy Shih Arthur Choi Adnan Darwiche FAtt 74 243 0 09 May 2018
A Survey Of Methods For Explaining Black Box Models Riccardo Guidotti A. Monreale Salvatore Ruggieri Franco Turini D. Pedreschi F. Giannotti XAI 140 3,970 0 06 Feb 2018
Learning Explanatory Rules from Noisy Data Richard Evans Edward Grefenstette 124 487 0 13 Nov 2017
Deep Learning for Case-Based Reasoning through Prototypes: A Neural Network that Explains Its Predictions Oscar Li Hao Liu Chaofan Chen Cynthia Rudin 178 592 0 13 Oct 2017
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 293 2,267 0 24 Jun 2017
European Union regulations on algorithmic decision-making and a "right to explanation" B. Goodman Seth Flaxman FaML AILaw 67 1,903 0 28 Jun 2016
The Mythos of Model Interpretability Zachary Chase Lipton FaML 183 3,706 0 10 Jun 2016
How to Explain Individual Classification Decisions D. Baehrens T. Schroeter Stefan Harmeling M. Kawanabe K. Hansen K. Müller FAtt 140 1,104 0 06 Dec 2009