Learning Certifiably Optimal Rule Lists for Categorical Data

6 April 2017

Papers citing "Learning Certifiably Optimal Rule Lists for Categorical Data"

50 / 101 papers shown

Title
Efficient Exploration of the Rashomon Set of Rule Set Models Martino Ciaperoni Han Xiao A. Gionis 25 3 0 05 Jun 2024
Smooth Sensitivity for Learning Differentially-Private yet Accurate Rule Lists Timothée Ly Julien Ferry Marie-José Huguet Sébastien Gambs Ulrich Aïvodji 27 0 0 18 Mar 2024
Is Machine Learning Unsafe and Irresponsible in Social Sciences? Paradoxes and Reconsidering from Recidivism Prediction Tasks Jianhong Liu D. Li 13 1 0 11 Nov 2023
A Path to Simpler Models Starts With Noise Lesia Semenova Harry Chen Ronald E. Parr Cynthia Rudin 33 15 0 30 Oct 2023
CONFIDERAI: a novel CONFormal Interpretable-by-Design score function for Explainable and Reliable Artificial Intelligence Sara Narteni Alberto Carlevaro Fabrizio Dabbene M. Muselli Maurizio Mongelli 11 0 0 04 Sep 2023
Probabilistic Dataset Reconstruction from Interpretable Models Julien Ferry Ulrich Aïvodji Sébastien Gambs Marie-José Huguet Mohamed Siala 24 5 0 29 Aug 2023
Feature Importance Measurement based on Decision Tree Sampling Chao Huang Diptesh Das Koji Tsuda FAtt 16 2 0 25 Jul 2023
Learning Locally Interpretable Rule Ensemble Kentaro Kanamori 13 0 0 20 Jun 2023
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 30 8 0 06 Jun 2023
Rolling Lookahead Learning for Optimal Classification Trees Z. B. Organ Enis Kayış Taghi Khaniyev 13 0 0 21 Apr 2023
Practical Policy Optimization with Personalized Experimentation Mia Garrard Hanson Wang Benjamin Letham Shaun Singh Abbas Kazerouni ... Yin Huang Yichun Hu Chad Zhou Norm Zhou E. Bakshy 13 0 0 30 Mar 2023
A Seven-Layer Model for Standardising AI Fairness Assessment A. K. Agarwal Harshna Agarwal 20 0 0 21 Dec 2022
Logic-Based Explainability in Machine Learning João Marques-Silva LRM XAI 44 39 0 24 Oct 2022
Learning to Advise Humans in High-Stakes Settings Nicholas Wolczynski M. Saar-Tsechansky Tong Wang 23 0 0 23 Oct 2022
Self-explaining deep models with logic rule reasoning Seungeon Lee Xiting Wang Sungwon Han Xiaoyuan Yi Xing Xie M. Cha NAI ReLM LRM 27 16 0 13 Oct 2022
Fast Optimization of Weighted Sparse Decision Trees for use in Optimal Treatment Regimes and Optimal Policy Design Ali Behrouz Mathias Lécuyer Cynthia Rudin Margo Seltzer OffRL 15 2 0 13 Oct 2022
Explainable Global Fairness Verification of Tree-Based Classifiers Stefano Calzavara Lorenzo Cazzaro Claudio Lucchese Federico Marcuzzi 24 2 0 27 Sep 2022
Augmenting Interpretable Models with LLMs during Training Chandan Singh Armin Askari R. Caruana Jianfeng Gao 34 37 0 23 Sep 2022
A Scalable, Interpretable, Verifiable & Differentiable Logic Gate Convolutional Neural Network Architecture From Truth Tables Adrien Benamira Tristan Guérand Thomas Peyrin Trevor Yap Bryan Hooi 34 1 0 18 Aug 2022
Leveraging Explanations in Interactive Machine Learning: An Overview Stefano Teso Öznur Alkan Wolfgang Stammer Elizabeth M. Daly XAI FAtt LRM 26 62 0 29 Jul 2022
TalkToModel: Explaining Machine Learning Models with Interactive Natural Language Conversations Dylan Slack Satyapriya Krishna Himabindu Lakkaraju Sameer Singh 24 74 0 08 Jul 2022
Quant-BnB: A Scalable Branch-and-Bound Method for Optimal Decision Trees with Continuous Features Rahul Mazumder X. Meng Haoyue Wang 12 16 0 23 Jun 2022
Mixed integer linear optimization formulations for learning optimal binary classification trees B. Alston Hamidreza Validi Illya V. Hicks 11 3 0 10 Jun 2022
Learning Interpretable Decision Rule Sets: A Submodular Optimization Approach Fan Yang Kai He Linxiao Yang Hongxia Du Jingbang Yang Bo Yang Liangcheng Sun 13 21 0 08 Jun 2022
bsnsing: A decision tree induction method based on recursive optimal boolean rule composition Yan-ching Liu 27 6 0 30 May 2022
Computing the Collection of Good Models for Rule Lists Kota Mata Kentaro Kanamori Hiroki Arimura 11 7 0 24 Apr 2022
Learning Interpretable, High-Performing Policies for Autonomous Driving Rohan R. Paleja Yaru Niu Andrew Silva Chace Ritchie Sugju Choi Matthew C. Gombolay 19 16 0 04 Feb 2022
Fast Interpretable Greedy-Tree Sums Yan Shuo Tan Chandan Singh Keyan Nasseri Abhineet Agarwal James Duncan Omer Ronen M. Epland Aaron E. Kornblith Bin-Xia Yu AI4CE 27 6 0 28 Jan 2022
Differentiable Rule Induction with Learned Relational Features R. Kusters Yusik Kim Marine Collery C. Marie Shubham Gupta 24 14 0 17 Jan 2022
Interpretable and Fair Boolean Rule Sets via Column Generation Connor Lawless S. Dash Oktay Gunluk Dennis L. Wei FaML 18 12 0 16 Nov 2021
The Impact of Algorithmic Risk Assessments on Human Predictions and its Analysis via Crowdsourcing Studies Riccardo Fogliato Alexandra Chouldechova Zachary Chase Lipton 24 31 0 03 Sep 2021
FADE: FAir Double Ensemble Learning for Observable and Counterfactual Outcomes Alan Mishler Edward H. Kennedy FaML 27 23 0 01 Sep 2021
Quantifying Explainability in NLP and Analyzing Algorithms for Performance-Explainability Tradeoff Michael J. Naylor C. French Samantha R. Terker Uday Kamath 36 10 0 12 Jul 2021
Fair Decision Rules for Binary Classification Connor Lawless Oktay Gunluk FaML 26 6 0 03 Jul 2021
Characterizing the risk of fairwashing Ulrich Aïvodji Hiromi Arai Sébastien Gambs Satoshi Hara 23 27 0 14 Jun 2021
Entropy-based Logic Explanations of Neural Networks Pietro Barbiero Gabriele Ciravegna Francesco Giannini Pietro Lió Marco Gori S. Melacci FAtt XAI 25 78 0 12 Jun 2021
Information-theoretic Evolution of Model Agnostic Global Explanations Sukriti Verma Nikaash Puri Piyush B. Gupta Balaji Krishnamurthy FAtt 24 0 0 14 May 2021
SAT-Based Rigorous Explanations for Decision Lists Alexey Ignatiev João Marques-Silva XAI 9 44 0 14 May 2021
Human strategic decision making in parametrized games Sam Ganzfried 11 0 0 30 Apr 2021
Robust subgroup discovery Hugo Manuel Proença Peter Grünwald Thomas Bäck M. Leeuwen 23 11 0 25 Mar 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 59 653 0 20 Mar 2021
A Scalable Two Stage Approach to Computing Optimal Decision Sets Alexey Ignatiev Edward Lam Peter James Stuckey João Marques-Silva 6 14 0 03 Feb 2021
Bayesian Pyramids: Identifiable Multilayer Discrete Latent Structure Models for Discrete Data Yuqi Gu David B. Dunson 32 19 0 25 Jan 2021
Distilling Interpretable Models into Human-Readable Code Walker Ravina Ethan Sterling Olexiy Oryeshko Nathan Bell Honglei Zhuang Xuanhui Wang Yonghui Wu Alexander Grushetsky 30 2 0 21 Jan 2021
Better Short than Greedy: Interpretable Models through Optimal Rule Boosting Mario Boley Simon Teshuva P. L. Bodic Geoffrey I. Webb 13 5 0 21 Jan 2021
GLocalX -- From Local to Global Explanations of Black Box AI Models Mattia Setzu Riccardo Guidotti A. Monreale Franco Turini D. Pedreschi F. Giannotti 11 116 0 19 Jan 2021
Explainable AI and Adoption of Financial Algorithmic Advisors: an Experimental Study D. David Yehezkel S. Resheff Talia Tron 13 23 0 05 Jan 2021
MAIRE -- A Model-Agnostic Interpretable Rule Extraction Procedure for Explaining Classifiers Rajat Sharma N. Reddy V. Kamakshi N. C. Krishnan Shweta Jain FAtt 17 7 0 03 Nov 2020
On Explaining Decision Trees Yacine Izza Alexey Ignatiev João Marques-Silva FAtt 16 84 0 21 Oct 2020
Optimal Decision Lists using SAT Jinqiang Yu Alexey Ignatiev P. L. Bodic Peter James Stuckey 20 9 0 19 Oct 2020