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Towards Explainable Artificial Intelligence (XAI): A Data Mining Perspective

9 January 2024

Haoyi Xiong

Papers citing "Towards Explainable Artificial Intelligence (XAI): A Data Mining Perspective"

30 / 80 papers shown

Title
A Survey on Explainable Artificial Intelligence (XAI): Towards Medical XAI Erico Tjoa Cuntai Guan XAI 122 1,452 0 17 Jul 2019
A study on the Interpretability of Neural Retrieval Models using DeepSHAP Zeon Trevor Fernando Jaspreet Singh Avishek Anand FAtt AAML 54 68 0 15 Jul 2019
The What-If Tool: Interactive Probing of Machine Learning Models James Wexler Mahima Pushkarna Tolga Bolukbasi Martin Wattenberg F. Viégas Jimbo Wilson VLM 81 495 0 09 Jul 2019
Does Learning Require Memorization? A Short Tale about a Long Tail Vitaly Feldman TDI 142 502 0 12 Jun 2019
Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned Elena Voita David Talbot F. Moiseev Rico Sennrich Ivan Titov 119 1,148 0 23 May 2019
Adversarial Examples Are Not Bugs, They Are Features Andrew Ilyas Shibani Santurkar Dimitris Tsipras Logan Engstrom Brandon Tran Aleksander Madry SILM 95 1,845 0 06 May 2019
Heavy-Tailed Universality Predicts Trends in Test Accuracies for Very Large Pre-Trained Deep Neural Networks Charles H. Martin Michael W. Mahoney 73 56 0 24 Jan 2019
ULDor: A Universal Lesion Detector for CT Scans with Pseudo Masks and Hard Negative Example Mining Youbao Tang Ke Yan Yuxing Tang Jiamin Liu Jing Xiao Ronald M. Summers MedIm 111 61 0 18 Jan 2019
An Empirical Study of Example Forgetting during Deep Neural Network Learning Mariya Toneva Alessandro Sordoni Rémi Tachet des Combes Adam Trischler Yoshua Bengio Geoffrey J. Gordon 134 741 0 12 Dec 2018
Implicit Self-Regularization in Deep Neural Networks: Evidence from Random Matrix Theory and Implications for Learning Charles H. Martin Michael W. Mahoney AI4CE 123 201 0 02 Oct 2018
This Looks Like That: Deep Learning for Interpretable Image Recognition Chaofan Chen Oscar Li Chaofan Tao A. Barnett Jonathan Su Cynthia Rudin 255 1,187 0 27 Jun 2018
Learning Adversarially Fair and Transferable Representations David Madras Elliot Creager T. Pitassi R. Zemel FaML 384 685 0 17 Feb 2018
A Survey Of Methods For Explaining Black Box Models Riccardo Guidotti A. Monreale Salvatore Ruggieri Franco Turini D. Pedreschi F. Giannotti XAI 150 3,979 0 06 Feb 2018
Interpreting CNNs via Decision Trees Quanshi Zhang Yu Yang Ying Nian Wu Song-Chun Zhu FAtt 73 323 0 01 Feb 2018
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV) Been Kim Martin Wattenberg Justin Gilmer Carrie J. Cai James Wexler F. Viégas Rory Sayres FAtt 248 1,849 0 30 Nov 2017
Distilling a Neural Network Into a Soft Decision Tree Nicholas Frosst Geoffrey E. Hinton 430 639 0 27 Nov 2017
Interpreting Deep Visual Representations via Network Dissection Bolei Zhou David Bau A. Oliva Antonio Torralba FAtt MILM 63 325 0 15 Nov 2017
Grad-CAM++: Improved Visual Explanations for Deep Convolutional Networks Aditya Chattopadhyay Anirban Sarkar Prantik Howlader V. Balasubramanian FAtt 119 2,311 0 30 Oct 2017
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 1.1K 22,090 0 22 May 2017
Network Dissection: Quantifying Interpretability of Deep Visual Representations David Bau Bolei Zhou A. Khosla A. Oliva Antonio Torralba MILM FAtt 158 1,526 1 19 Apr 2017
Learning Important Features Through Propagating Activation Differences Avanti Shrikumar Peyton Greenside A. Kundaje FAtt 203 3,884 0 10 Apr 2017
Understanding Black-box Predictions via Influence Functions Pang Wei Koh Percy Liang TDI 219 2,910 0 14 Mar 2017
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization Ramprasaath R. Selvaraju Michael Cogswell Abhishek Das Ramakrishna Vedantam Devi Parikh Dhruv Batra FAtt 335 20,110 0 07 Oct 2016
Training Region-based Object Detectors with Online Hard Example Mining Abhinav Shrivastava Abhinav Gupta Ross B. Girshick ObjD 157 2,422 0 12 Apr 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 1.2K 17,071 0 16 Feb 2016
Learning Deep Features for Discriminative Localization Bolei Zhou A. Khosla Àgata Lapedriza A. Oliva Antonio Torralba SSL SSeg FAtt 253 9,342 0 14 Dec 2015
Understanding Deep Image Representations by Inverting Them Aravindh Mahendran Andrea Vedaldi FAtt 131 1,968 0 26 Nov 2014
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps Karen Simonyan Andrea Vedaldi Andrew Zisserman FAtt 317 7,321 0 20 Dec 2013
Visualizing and Understanding Convolutional Networks Matthew D. Zeiler Rob Fergus FAtt SSL 603 15,907 0 12 Nov 2013
Identifying Mislabeled Training Data C. Brodley M. Friedl 111 972 0 01 Jun 2011