Interpretability via Model Extraction

29 June 2017

Papers citing "Interpretability via Model Extraction"

30 / 30 papers shown

Title
Recent Advances in Malware Detection: Graph Learning and Explainability Hossein Shokouhinejad Roozbeh Razavi-Far Hesamodin Mohammadian Mahdi Rabbani Samuel Ansong Griffin Higgins Ali Ghorbani AAML 76 2 0 14 Feb 2025
Leveraging Historical Medical Records as a Proxy via Multimodal Modeling and Visualization to Enrich Medical Diagnostic Learning Ouyang Yang Yuchen Wu He Wang Chenyang Zhang Furui Cheng Chang Jiang Lixia Jin Yuanwu Cao Qu Li 16 6 0 23 Jul 2023
Interpretable Differencing of Machine Learning Models Swagatam Haldar Diptikalyan Saha Dennis L. Wei Rahul Nair Elizabeth M. Daly 16 1 0 10 Jun 2023
Implementing Responsible AI: Tensions and Trade-Offs Between Ethics Aspects Conrad Sanderson David M. Douglas Qinghua Lu 43 12 0 17 Apr 2023
Concept Learning for Interpretable Multi-Agent Reinforcement Learning Renos Zabounidis Joseph Campbell Simon Stepputtis Dana Hughes Katia P. Sycara 39 15 0 23 Feb 2023
Logic-Based Explainability in Machine Learning Sasha Rubin LRM XAI 50 39 0 24 Oct 2022
Superpolynomial Lower Bounds for Decision Tree Learning and Testing Caleb M. Koch Carmen Strassle Li-Yang Tan 32 8 0 12 Oct 2022
A Human-Centric Take on Model Monitoring Murtuza N. Shergadwala Himabindu Lakkaraju K. Kenthapadi 43 9 0 06 Jun 2022
Neural Basis Models for Interpretability Filip Radenovic Abhimanyu Dubey D. Mahajan FAtt 32 46 0 27 May 2022
The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective Satyapriya Krishna Tessa Han Alex Gu Steven Wu S. Jabbari Himabindu Lakkaraju 186 186 0 03 Feb 2022
Forward Composition Propagation for Explainable Neural Reasoning Isel Grau Gonzalo Nápoles M. Bello Yamisleydi Salgueiro A. Jastrzębska 22 0 0 23 Dec 2021
Model Doctor: A Simple Gradient Aggregation Strategy for Diagnosing and Treating CNN Classifiers Zunlei Feng Jiacong Hu Sai Wu Xiaotian Yu Mingli Song Xiuming Zhang 40 13 0 09 Dec 2021
Provably efficient, succinct, and precise explanations Guy Blanc Jane Lange Li-Yang Tan FAtt 37 35 0 01 Nov 2021
Counterfactuals and Causability in Explainable Artificial Intelligence: Theory, Algorithms, and Applications Yu-Liang Chou Catarina Moreira P. Bruza Chun Ouyang Joaquim A. Jorge CML 47 176 0 07 Mar 2021
Why model why? Assessing the strengths and limitations of LIME Jurgen Dieber S. Kirrane FAtt 26 97 0 30 Nov 2020
Robust and Stable Black Box Explanations Himabindu Lakkaraju Nino Arsov Osbert Bastani AAML FAtt 24 84 0 12 Nov 2020
On Explaining Decision Trees Yacine Izza Alexey Ignatiev Sasha Rubin FAtt 24 85 0 21 Oct 2020
Contextual Semantic Interpretability Diego Marcos Ruth C. Fong Sylvain Lobry Rémi Flamary Nicolas Courty D. Tuia SSL 20 27 0 18 Sep 2020
Beyond Individualized Recourse: Interpretable and Interactive Summaries of Actionable Recourses Kaivalya Rawal Himabindu Lakkaraju 27 11 0 15 Sep 2020
Generative causal explanations of black-box classifiers Matthew R. O’Shaughnessy Gregory H. Canal Marissa Connor Mark A. Davenport Christopher Rozell CML 30 73 0 24 Jun 2020
Born-Again Tree Ensembles Thibaut Vidal Toni Pacheco Maximilian Schiffer 62 53 0 24 Mar 2020
Interpretability of Blackbox Machine Learning Models through Dataview Extraction and Shadow Model creation Rupam Patir Shubham Singhal C. Anantaram Vikram Goyal 13 0 0 02 Feb 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 52 702 0 08 Jan 2020
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI Alejandro Barredo Arrieta Natalia Díaz Rodríguez Javier Del Ser Adrien Bennetot Siham Tabik ... S. Gil-Lopez Daniel Molina Richard Benjamins Raja Chatila Francisco Herrera XAI 37 6,111 0 22 Oct 2019
A framework for the extraction of Deep Neural Networks by leveraging public data Soham Pal Yash Gupta Aditya Shukla Aditya Kanade S. Shevade V. Ganapathy FedML MLAU MIACV 36 56 0 22 May 2019
Interpretable Deep Learning under Fire Xinyang Zhang Ningfei Wang Hua Shen S. Ji Xiapu Luo Ting Wang AAML AI4CE 22 169 0 03 Dec 2018
A Gradient-Based Split Criterion for Highly Accurate and Transparent Model Trees Klaus Broelemann Gjergji Kasneci 24 20 0 25 Sep 2018
Techniques for Interpretable Machine Learning Mengnan Du Ninghao Liu Xia Hu FaML 39 1,071 0 31 Jul 2018
Interpreting Neural Network Judgments via Minimal, Stable, and Symbolic Corrections Xin Zhang Armando Solar-Lezama Rishabh Singh FAtt 21 63 0 21 Feb 2018