An Optimization Approach to Learning Falling Rule Lists

6 October 2017

Papers citing "An Optimization Approach to Learning Falling Rule Lists"

10 / 10 papers shown

Title
Interpretable Reinforcement Learning for Robotics and Continuous Control Rohan R. Paleja Letian Chen Yaru Niu Andrew Silva Zhaoxin Li ... K. Chang H. E. Tseng Yan Wang S. Nageshrao Matthew C. Gombolay 34 7 0 16 Nov 2023
Logic-Based Explainability in Machine Learning Sasha Rubin LRM XAI 50 39 0 24 Oct 2022
Learning Interpretable, High-Performing Policies for Autonomous Driving Rohan R. Paleja Yaru Niu Andrew Silva Chace Ritchie Sugju Choi Matthew C. Gombolay 21 16 0 04 Feb 2022
SAT-Based Rigorous Explanations for Decision Lists Alexey Ignatiev Sasha Rubin XAI 25 44 0 14 May 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
Interpretability and Explainability: A Machine Learning Zoo Mini-tour Ricards Marcinkevics Julia E. Vogt XAI 28 119 0 03 Dec 2020
On Explaining Decision Trees Yacine Izza Alexey Ignatiev Sasha Rubin FAtt 24 85 0 21 Oct 2020
LIBRE: Learning Interpretable Boolean Rule Ensembles Graziano Mita Paolo Papotti Maurizio Filippone Pietro Michiardi 8 16 0 15 Nov 2019
Learning Certifiably Optimal Rule Lists for Categorical Data E. Angelino Nicholas Larus-Stone Daniel Alabi Margo Seltzer Cynthia Rudin 60 195 0 06 Apr 2017
Learning Optimized Risk Scores Berk Ustun Cynthia Rudin 17 82 0 01 Oct 2016