MLIC: A MaxSAT-Based framework for learning interpretable classification rules

5 December 2018

Papers citing "MLIC: A MaxSAT-Based framework for learning interpretable classification rules"

20 / 20 papers shown

Title
Reasoning in Neurosymbolic AI Son N. Tran E. Mota Artur Garcez NAI 22 0 0 22 May 2025
Certifying Pareto-Optimality in Multi-Objective Maximum Satisfiability Christoph Jabs Jeremias Berg Bart Bogaerts Matti Järvisalo 40 1 0 29 Jan 2025
Efficient Exploration of the Rashomon Set of Rule Set Models Martino Ciaperoni Han Xiao Aristides Gionis 75 4 0 05 Jun 2024
An Incremental MaxSAT-based Model to Learn Interpretable and Balanced Classification Rules Antônio Carlos Souza Ferreira Júnior Thiago Alves Rocha 64 0 0 25 Mar 2024
Explainable AI using expressive Boolean formulas G. Rosenberg J. K. Brubaker M. Schuetz Grant Salton Zhihuai Zhu E. Zhu Serdar Kadioğlu S. E. Borujeni H. Katzgraber 58 8 0 06 Jun 2023
DeepSaDe: Learning Neural Networks that Guarantee Domain Constraint Satisfaction Kshitij Goyal Sebastijan Dumancic Hendrik Blockeel 70 2 0 02 Mar 2023
Logic-Based Explainability in Machine Learning Sasha Rubin LRM XAI 126 40 0 24 Oct 2022
Eliminating The Impossible, Whatever Remains Must Be True Jinqiang Yu Alexey Ignatiev Peter Stuckey Nina Narodytska Sasha Rubin 89 23 0 20 Jun 2022
Efficient Learning of Interpretable Classification Rules Bishwamittra Ghosh Dmitry Malioutov Kuldeep S. Meel 57 8 0 14 May 2022
Learning MAX-SAT from Contextual Examples for Combinatorial Optimisation Mohit Kumar Samuel Kolb Stefano Teso Luc de Raedt NAI 30 14 0 08 Feb 2022
SaDe: Learning Models that Provably Satisfy Domain Constraints Kshitij Goyal Sebastijan Dumancic Hendrik Blockeel ALM 60 5 0 01 Dec 2021
Rule Generation for Classification: Scalability, Interpretability, and Fairness Tabea E. Rober Adia C. Lumadjeng M. Akyuz cS. .Ilker Birbil 111 2 0 21 Apr 2021
Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges Cynthia Rudin Chaofan Chen Zhi Chen Haiyang Huang Lesia Semenova Chudi Zhong FaML AI4CE LRM 240 675 0 20 Mar 2021
A Scalable Two Stage Approach to Computing Optimal Decision Sets Alexey Ignatiev Edward Lam Peter Stuckey Sasha Rubin 36 14 0 03 Feb 2021
Justicia: A Stochastic SAT Approach to Formally Verify Fairness Bishwamittra Ghosh D. Basu Kuldeep S. Meel 159 41 0 14 Sep 2020
Computing Optimal Decision Sets with SAT Jinqiang Yu Alexey Ignatiev Peter Stuckey P. L. Bodic FAtt 114 26 0 29 Jul 2020
IMLI: An Incremental Framework for MaxSAT-Based Learning of Interpretable Classification Rules Bishwamittra Ghosh Kuldeep S. Meel 75 35 0 07 Jan 2020
From Shallow to Deep Interactions Between Knowledge Representation, Reasoning and Machine Learning (Kay R. Amel group) Zied Bouraoui Antoine Cornuéjols Thierry Denoeux Sebastien Destercke Didier Dubois ... Jérôme Mengin H. Prade Steven Schockaert M. Serrurier Christel Vrain 128 14 0 13 Dec 2019
Neural-Symbolic Descriptive Action Model from Images: The Search for STRIPS Masataro Asai 58 4 0 11 Dec 2019
Advances in Machine Learning for the Behavioral Sciences Tomáš Kliegr Š. Bahník Johannes Furnkranz 38 14 0 08 Nov 2019