Understanding Black-box Predictions via Influence Functions

14 March 2017

Pang Wei Koh

Papers citing "Understanding Black-box Predictions via Influence Functions"

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Title
Explaining Vulnerabilities of Deep Learning to Adversarial Malware Binaries Christian Scano Battista Biggio Giovanni Lagorio Fabio Roli A. Armando AAML 24 129 0 11 Jan 2019
Interpretable CNNs for Object Classification Quanshi Zhang Xin Eric Wang Ying Nian Wu Huilin Zhou Song-Chun Zhu 24 54 0 08 Jan 2019
Contamination Attacks and Mitigation in Multi-Party Machine Learning Jamie Hayes O. Ohrimenko AAML FedML 25 74 0 08 Jan 2019
Explaining AlphaGo: Interpreting Contextual Effects in Neural Networks Zenan Ling Haotian Ma Yu Yang Robert C. Qiu Song-Chun Zhu Quanshi Zhang MILM 14 3 0 08 Jan 2019
Can You Trust This Prediction? Auditing Pointwise Reliability After Learning Peter F. Schulam Suchi Saria OOD 27 103 0 02 Jan 2019
Soft Autoencoder and Its Wavelet Adaptation Interpretation Fenglei Fan Mengzhou Li Yueyang Teng Ge Wang 24 3 0 31 Dec 2018
Mining Interpretable AOG Representations from Convolutional Networks via Active Question Answering Quanshi Zhang Ruiming Cao Ying Nian Wu Song-Chun Zhu 19 14 0 18 Dec 2018
Explaining Neural Networks Semantically and Quantitatively Runjin Chen Hao Chen Ge Huang Jie Ren Quanshi Zhang FAtt 23 54 0 18 Dec 2018
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 46 715 0 12 Dec 2018
Analyzing Federated Learning through an Adversarial Lens A. Bhagoji Supriyo Chakraborty Prateek Mittal S. Calo FedML 191 1,034 0 29 Nov 2018
How to improve the interpretability of kernel learning Jinwei Zhao Qizhou Wang Yufei Wang Yu Liu Zhenghao Shi Xinhong Hei FAtt 22 0 0 21 Nov 2018
Explaining Deep Learning Models - A Bayesian Non-parametric Approach Wenbo Guo Sui Huang Yunzhe Tao Masashi Sugiyama Lin Lin BDL 16 47 0 07 Nov 2018
Stronger Data Poisoning Attacks Break Data Sanitization Defenses Pang Wei Koh Jacob Steinhardt Percy Liang 6 240 0 02 Nov 2018
Interpreting Black Box Predictions using Fisher Kernels Rajiv Khanna Been Kim Joydeep Ghosh Oluwasanmi Koyejo FAtt 27 103 0 23 Oct 2018
Efficient Augmentation via Data Subsampling Michael Kuchnik Virginia Smith 27 22 0 11 Oct 2018
Understanding the Origins of Bias in Word Embeddings Marc-Etienne Brunet Colleen Alkalay-Houlihan Ashton Anderson R. Zemel FaML 26 198 0 08 Oct 2018
Visually Communicating and Teaching Intuition for Influence Functions Aaron Fisher Edward H. Kennedy 27 51 0 08 Oct 2018
SNIP: Single-shot Network Pruning based on Connection Sensitivity Namhoon Lee Thalaiyasingam Ajanthan Philip Torr VLM 96 1,176 0 04 Oct 2018
Training Machine Learning Models by Regularizing their Explanations A. Ross FaML 26 0 0 29 Sep 2018
Stakeholders in Explainable AI Alun D. Preece Daniel Harborne Dave Braines Richard J. Tomsett Supriyo Chakraborty 15 154 0 29 Sep 2018
Response Characterization for Auditing Cell Dynamics in Long Short-term Memory Networks Ramin M. Hasani Alexander Amini Mathias Lechner Felix Naser Radu Grosu Daniela Rus 28 25 0 11 Sep 2018
Why Do Adversarial Attacks Transfer? Explaining Transferability of Evasion and Poisoning Attacks Ambra Demontis Marco Melis Maura Pintor Matthew Jagielski Battista Biggio Alina Oprea Cristina Nita-Rotaru Fabio Roli SILM AAML 19 11 0 08 Sep 2018
Interpreting Neural Networks With Nearest Neighbors Eric Wallace Shi Feng Jordan L. Boyd-Graber AAML FAtt MILM 23 53 0 08 Sep 2018
Zero-shot Transfer Learning for Semantic Parsing J. Dadashkarimi Alexander R. Fabbri S. Tatikonda Dragomir R. Radev 23 4 0 27 Aug 2018
XAI Beyond Classification: Interpretable Neural Clustering Xi Peng Yunfan Li Ivor W. Tsang Erik Cambria Jiancheng Lv Qiufeng Wang 29 74 0 22 Aug 2018
Are You Tampering With My Data? Michele Alberti Vinaychandran Pondenkandath Marcel Würsch Manuel Bouillon Mathias Seuret Rolf Ingold Marcus Liwicki AAML 37 19 0 21 Aug 2018
Reinforcement Learning for Autonomous Defence in Software-Defined Networking Yi Han Benjamin I. P. Rubinstein Tamas Abraham T. Alpcan O. Vel S. Erfani David Hubczenko C. Leckie Paul Montague AAML 22 68 0 17 Aug 2018
Sequence to Logic with Copy and Cache J. Dadashkarimi S. Tatikonda 33 0 0 19 Jul 2018
Automated Data Slicing for Model Validation:A Big data - AI Integration Approach Yeounoh Chung Tim Kraska N. Polyzotis Ki Hyun Tae Steven Euijong Whang 19 129 0 16 Jul 2018
Learning Implicit Generative Models by Teaching Explicit Ones Chao Du Kun Xu Chongxuan Li Jun Zhu Bo Zhang DRL GAN 14 9 0 10 Jul 2018
Model Agnostic Supervised Local Explanations Gregory Plumb Denali Molitor Ameet Talwalkar FAtt LRM MILM 14 196 0 09 Jul 2018
Optimal Piecewise Local-Linear Approximations Kartik Ahuja W. Zame M. Schaar FAtt 27 1 0 27 Jun 2018
Optimizing the Wisdom of the Crowd: Inference, Learning, and Teaching Yao Zhou Jingrui He NoLa 16 7 0 23 Jun 2018
xGEMs: Generating Examplars to Explain Black-Box Models Shalmali Joshi Oluwasanmi Koyejo Been Kim Joydeep Ghosh MLAU 25 40 0 22 Jun 2018
Visualizing and Understanding Deep Neural Networks in CTR Prediction Lin Guo Hui Ye Wenbo Su He Liu Kai Sun Hang Xiang FAtt HAI 10 7 0 22 Jun 2018
DeepAffinity: Interpretable Deep Learning of Compound-Protein Affinity through Unified Recurrent and Convolutional Neural Networks Mostafa Karimi Di Wu Zhangyang Wang Yang Shen 35 358 0 20 Jun 2018
Defining Locality for Surrogates in Post-hoc Interpretablity Thibault Laugel X. Renard Marie-Jeanne Lesot Christophe Marsala Marcin Detyniecki FAtt 15 80 0 19 Jun 2018
Hierarchical interpretations for neural network predictions Chandan Singh W. James Murdoch Bin Yu 31 145 0 14 Jun 2018
Representation Learning on Graphs with Jumping Knowledge Networks Keyulu Xu Chengtao Li Yonglong Tian Tomohiro Sonobe Ken-ichi Kawarabayashi Stefanie Jegelka GNN 279 1,948 0 09 Jun 2018
Minnorm training: an algorithm for training over-parameterized deep neural networks Yamini Bansal Madhu S. Advani David D. Cox Andrew M. Saxe ODL 15 18 0 03 Jun 2018
Explainable Recommendation: A Survey and New Perspectives Yongfeng Zhang Xu Chen XAI LRM 52 866 0 30 Apr 2018
Seq2Seq-Vis: A Visual Debugging Tool for Sequence-to-Sequence Models Hendrik Strobelt Sebastian Gehrmann M. Behrisch Adam Perer Hanspeter Pfister Alexander M. Rush VLM HAI 31 239 0 25 Apr 2018
Disentangling Controllable and Uncontrollable Factors of Variation by Interacting with the World Yoshihide Sawada DRL 21 10 0 19 Apr 2018
Understanding Community Structure in Layered Neural Networks C. Watanabe Kaoru Hiramatsu K. Kashino 19 22 0 13 Apr 2018
Visual Analytics for Explainable Deep Learning Jaegul Choo Shixia Liu HAI XAI 22 235 0 07 Apr 2018
Learning to Reweight Examples for Robust Deep Learning Mengye Ren Wenyuan Zeng Binh Yang R. Urtasun OOD NoLa 69 1,412 0 24 Mar 2018
Explanation Methods in Deep Learning: Users, Values, Concerns and Challenges Gabrielle Ras Marcel van Gerven W. Haselager XAI 17 217 0 20 Mar 2018
Technical Report: When Does Machine Learning FAIL? Generalized Transferability for Evasion and Poisoning Attacks Octavian Suciu R. Marginean Yigitcan Kaya Hal Daumé Tudor Dumitras AAML 40 286 0 19 Mar 2018
Explaining Black-box Android Malware Detection Marco Melis Davide Maiorca Battista Biggio Giorgio Giacinto Fabio Roli AAML FAtt 9 43 0 09 Mar 2018
The Challenge of Crafting Intelligible Intelligence Daniel S. Weld Gagan Bansal 26 241 0 09 Mar 2018