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[1] Wen-Chuan Lee,et al. MODE: automated neural network model debugging via state differential analysis and input selection , 2018, ESEC/SIGSOFT FSE.
[2] Bolei Zhou,et al. Learning Deep Features for Discriminative Localization , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[3] Alper Sen,et al. DeepFault: Fault Localization for Deep Neural Networks , 2019, FASE.
[4] Pascal Vincent,et al. Representation Learning: A Review and New Perspectives , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[5] Xiang Gao,et al. Fuzz Testing based Data Augmentation to Improve Robustness of Deep Neural Networks , 2020, 2020 IEEE/ACM 42nd International Conference on Software Engineering (ICSE).
[6] Jeffrey Byrne,et al. Visualizing and Quantifying Discriminative Features for Face Recognition , 2018, 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018).
[7] Yarin Gal,et al. Real Time Image Saliency for Black Box Classifiers , 2017, NIPS.
[8] Robert R. Sokal,et al. A statistical method for evaluating systematic relationships , 1958 .
[9] Yale Song,et al. Fast, Cheap, and Good: Why Animated GIFs Engage Us , 2016, CHI.
[10] David E. Irwin,et al. Finding a "Kneedle" in a Haystack: Detecting Knee Points in System Behavior , 2011, 2011 31st International Conference on Distributed Computing Systems Workshops.
[11] Anima Anandkumar,et al. Deep Active Learning for Named Entity Recognition , 2017, Rep4NLP@ACL.
[12] Gabriele Bavota,et al. Taxonomy of Real Faults in Deep Learning Systems , 2019, 2020 IEEE/ACM 42nd International Conference on Software Engineering (ICSE).
[13] Alexander Binder,et al. Explaining nonlinear classification decisions with deep Taylor decomposition , 2015, Pattern Recognit..
[14] J. H. Ward. Hierarchical Grouping to Optimize an Objective Function , 1963 .
[15] Klaus-Robert Müller,et al. Layer-Wise Relevance Propagation: An Overview , 2019, Explainable AI.
[16] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[17] Fionn Murtagh,et al. Ward’s Hierarchical Agglomerative Clustering Method: Which Algorithms Implement Ward’s Criterion? , 2011, Journal of Classification.
[18] Abhishek Das,et al. Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization , 2016, 2017 IEEE International Conference on Computer Vision (ICCV).
[19] M. J. van der Laan,et al. A new partitioning around medoids algorithm , 2003 .
[20] Peter Robinson,et al. Learning an appearance-based gaze estimator from one million synthesised images , 2016, ETRA.
[21] Thomas Brox,et al. Striving for Simplicity: The All Convolutional Net , 2014, ICLR.
[22] Aleksander Madry,et al. Exploring the Landscape of Spatial Robustness , 2017, ICML.
[23] Alexander Binder,et al. Evaluating the Visualization of What a Deep Neural Network Has Learned , 2015, IEEE Transactions on Neural Networks and Learning Systems.
[24] B. Fornberg. Generation of finite difference formulas on arbitrarily spaced grids , 1988 .
[25] Lionel C. Briand,et al. A practical guide for using statistical tests to assess randomized algorithms in software engineering , 2011, 2011 33rd International Conference on Software Engineering (ICSE).
[26] Kang Ryoung Park,et al. Deep Learning-Based Gaze Detection System for Automobile Drivers Using a NIR Camera Sensor , 2018, Sensors.
[27] J. MacQueen. Some methods for classification and analysis of multivariate observations , 1967 .
[28] Shin Yoo,et al. Guiding Deep Learning System Testing Using Surprise Adequacy , 2018, 2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE).
[29] Lukas Jendele,et al. Efficient Automated Decomposition of Build Targets at Large-Scale , 2019, 2019 12th IEEE Conference on Software Testing, Validation and Verification (ICST).
[30] A. Vargha,et al. A Critique and Improvement of the CL Common Language Effect Size Statistics of McGraw and Wong , 2000 .
[31] Burr Settles,et al. Active Learning , 2012, Synthesis Lectures on Artificial Intelligence and Machine Learning.
[32] Ronald S. King,et al. Cluster Analysis and Data Mining: An Introduction , 2014 .
[33] Kaixin Sui,et al. Generic and Robust Localization of Multi-dimensional Root Causes , 2019, 2019 IEEE 30th International Symposium on Software Reliability Engineering (ISSRE).
[34] Rob Fergus,et al. Visualizing and Understanding Convolutional Networks , 2013, ECCV.
[35] Hao Zhang,et al. Apricot: A Weight-Adaptation Approach to Fixing Deep Learning Models , 2019, 2019 34th IEEE/ACM International Conference on Automated Software Engineering (ASE).
[36] Kate Saenko,et al. RISE: Randomized Input Sampling for Explanation of Black-box Models , 2018, BMVC.
[37] R. L. Thorndike. Who belongs in the family? , 1953 .
[38] Carlos Guestrin,et al. Anchors: High-Precision Model-Agnostic Explanations , 2018, AAAI.
[39] Xiaogang Wang,et al. Deep Learning Face Attributes in the Wild , 2014, 2015 IEEE International Conference on Computer Vision (ICCV).
[40] Divya Gopinath,et al. Property Inference for Deep Neural Networks , 2019, 2019 34th IEEE/ACM International Conference on Automated Software Engineering (ASE).
[41] Daniel Kroening,et al. A survey of safety and trustworthiness of deep neural networks: Verification, testing, adversarial attack and defence, and interpretability , 2018, Comput. Sci. Rev..
[42] Silvio Savarese,et al. Active Learning for Convolutional Neural Networks: A Core-Set Approach , 2017, ICLR.
[43] Jia Deng,et al. Stacked Hourglass Networks for Human Pose Estimation , 2016, ECCV.
[44] Jim Tørresen,et al. A task-and-technique centered survey on visual analytics for deep learning model engineering , 2018, Comput. Graph..
[45] Mark Harman,et al. Machine Learning Testing: Survey, Landscapes and Horizons , 2019, IEEE Transactions on Software Engineering.
[46] Fionn Murtagh,et al. Algorithms for hierarchical clustering: an overview , 2012, WIREs Data Mining Knowl. Discov..