Local Rule-Based Explanations of Black Box Decision Systems

28 May 2018

Papers citing "Local Rule-Based Explanations of Black Box Decision Systems"

42 / 192 papers shown

Title
Accurate and Intuitive Contextual Explanations using Linear Model Trees Aditya Lahiri N. Edakunni FAtt 6 2 0 11 Sep 2020
Explainable Artificial Intelligence for Process Mining: A General Overview and Application of a Novel Local Explanation Approach for Predictive Process Monitoring Nijat Mehdiyev Peter Fettke AI4TS 25 55 0 04 Sep 2020
Can We Trust Your Explanations? Sanity Checks for Interpreters in Android Malware Analysis Ming Fan Wenying Wei Xiaofei Xie Yang Liu X. Guan Ting Liu FAtt AAML 14 36 0 13 Aug 2020
Causality Learning: A New Perspective for Interpretable Machine Learning Guandong Xu Tri Dung Duong Q. Li S. Liu Xianzhi Wang XAI OOD CML 8 51 0 27 Jun 2020
Explaining Predictions by Approximating the Local Decision Boundary G. Vlassopoulos T. Erven Henry Brighton Vlado Menkovski FAtt 17 8 0 14 Jun 2020
Explainable Matrix -- Visualization for Global and Local Interpretability of Random Forest Classification Ensembles Mário Popolin Neto F. Paulovich FAtt 33 88 0 08 May 2020
Post-hoc explanation of black-box classifiers using confident itemsets M. Moradi Matthias Samwald 57 97 0 05 May 2020
A multi-component framework for the analysis and design of explainable artificial intelligence S. Atakishiyev H. Babiker Nawshad Farruque R. Goebel1 Myeongjung Kima M. H. Motallebi J. Rabelo T. Syed O. R. Zaïane 38 35 0 05 May 2020
Towards Interpretable ANNs: An Exact Transformation to Multi-Class Multivariate Decision Trees Duy T. Nguyen Kathryn E. Kasmarik H. Abbass 6 8 0 10 Mar 2020
Algorithmic Recourse: from Counterfactual Explanations to Interventions Amir-Hossein Karimi Bernhard Schölkopf Isabel Valera CML 24 337 0 14 Feb 2020
Convex Density Constraints for Computing Plausible Counterfactual Explanations André Artelt Barbara Hammer 19 47 0 12 Feb 2020
Interpretable Companions for Black-Box Models Dan-qing Pan Tong Wang Satoshi Hara FaML 12 8 0 10 Feb 2020
Black Box Explanation by Learning Image Exemplars in the Latent Feature Space Riccardo Guidotti A. Monreale Stan Matwin D. Pedreschi FAtt 6 67 0 27 Jan 2020
"Why is 'Chicago' deceptive?" Towards Building Model-Driven Tutorials for Humans Vivian Lai Han Liu Chenhao Tan 24 138 0 14 Jan 2020
On Interpretability of Artificial Neural Networks: A Survey Fenglei Fan Jinjun Xiong Mengzhou Li Ge Wang AAML AI4CE 38 300 0 08 Jan 2020
Questioning the AI: Informing Design Practices for Explainable AI User Experiences Q. V. Liao D. Gruen Sarah Miller 52 703 0 08 Jan 2020
Counterfactual Explanation Algorithms for Behavioral and Textual Data Yanou Ramon David Martens F. Provost Theodoros Evgeniou FAtt 15 87 0 04 Dec 2019
Automated Dependence Plots David I. Inouye Liu Leqi Joon Sik Kim Bryon Aragam Pradeep Ravikumar 12 1 0 02 Dec 2019
ACE -- An Anomaly Contribution Explainer for Cyber-Security Applications Xiao Zhang Manish Marwah I-Ta Lee M. Arlitt Dan Goldwasser 10 14 0 01 Dec 2019
FOCUS: Flexible Optimizable Counterfactual Explanations for Tree Ensembles Ana Lucic Harrie Oosterhuis H. Haned Maarten de Rijke LRM 6 61 0 27 Nov 2019
On the computation of counterfactual explanations -- A survey André Artelt Barbara Hammer LRM 22 50 0 15 Nov 2019
An Active Approach for Model Interpretation Jialin Lu Martin Ester 17 0 0 27 Oct 2019
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI Alejandro Barredo Arrieta Natalia Díaz Rodríguez Javier Del Ser Adrien Bennetot S. Tabik ... S. Gil-Lopez Daniel Molina Richard Benjamins Raja Chatila Francisco Herrera XAI 37 6,110 0 22 Oct 2019
Identifying the Most Explainable Classifier Brett Mullins FAtt 16 1 0 18 Oct 2019
MultiVerse: Causal Reasoning using Importance Sampling in Probabilistic Programming Yura N. Perov L. Graham Kostis Gourgoulias Jonathan G. Richens Ciarán M. Gilligan-Lee Adam Baker Saurabh Johri LRM 12 17 0 17 Oct 2019
Testing and verification of neural-network-based safety-critical control software: A systematic literature review Jin Zhang Jingyue Li 20 47 0 05 Oct 2019
REDS: Rule Extraction for Discovering Scenarios Vadim Arzamasov Klemens Böhm 11 6 0 03 Oct 2019
Interpreting Undesirable Pixels for Image Classification on Black-Box Models Sin-Han Kang Hong G Jung Seong-Whan Lee FAtt 14 3 0 27 Sep 2019
LoRMIkA: Local rule-based model interpretability with k-optimal associations Dilini Sewwandi Rajapaksha Christoph Bergmeir Wray L. Buntine 32 31 0 11 Aug 2019
Measurable Counterfactual Local Explanations for Any Classifier Adam White Artur Garcez FAtt 12 99 0 08 Aug 2019
Efficient computation of counterfactual explanations of LVQ models André Artelt Barbara Hammer 14 16 0 02 Aug 2019
The Dangers of Post-hoc Interpretability: Unjustified Counterfactual Explanations Thibault Laugel Marie-Jeanne Lesot Christophe Marsala X. Renard Marcin Detyniecki 14 194 0 22 Jul 2019
MoËT: Mixture of Expert Trees and its Application to Verifiable Reinforcement Learning Marko Vasic Andrija Petrović Kaiyuan Wang Mladen Nikolic Rishabh Singh S. Khurshid OffRL MoE 18 22 0 16 Jun 2019
LioNets: Local Interpretation of Neural Networks through Penultimate Layer Decoding Ioannis Mollas Nikolaos Bassiliades Grigorios Tsoumakas 14 12 0 15 Jun 2019
Issues with post-hoc counterfactual explanations: a discussion Thibault Laugel Marie-Jeanne Lesot Christophe Marsala Marcin Detyniecki CML 104 44 0 11 Jun 2019
CERTIFAI: Counterfactual Explanations for Robustness, Transparency, Interpretability, and Fairness of Artificial Intelligence models Shubham Sharma Jette Henderson Joydeep Ghosh 11 87 0 20 May 2019
Explaining Machine Learning Classifiers through Diverse Counterfactual Explanations R. Mothilal Amit Sharma Chenhao Tan CML 17 989 0 19 May 2019
An Interpretable Model with Globally Consistent Explanations for Credit Risk Chaofan Chen Kangcheng Lin Cynthia Rudin Yaron Shaposhnik Sijia Wang Tong Wang FAtt 7 93 0 30 Nov 2018
YASENN: Explaining Neural Networks via Partitioning Activation Sequences Yaroslav Zharov Denis Korzhenkov J. Lyu Alexander Tuzhilin FAtt AAML 6 6 0 07 Nov 2018
On The Stability of Interpretable Models Riccardo Guidotti Salvatore Ruggieri FAtt 16 10 0 22 Oct 2018
Open the Black Box Data-Driven Explanation of Black Box Decision Systems D. Pedreschi F. Giannotti Riccardo Guidotti A. Monreale Luca Pappalardo Salvatore Ruggieri Franco Turini 11 38 0 26 Jun 2018
A Survey Of Methods For Explaining Black Box Models Riccardo Guidotti A. Monreale Salvatore Ruggieri Franco Turini D. Pedreschi F. Giannotti XAI 17 3,903 0 06 Feb 2018