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
Towards Out-Of-Distribution Generalization: A Survey Jiashuo Liu Zheyan Shen Yue He Xingxuan Zhang Renzhe Xu Han Yu Peng Cui CML OOD 69 519 0 31 Aug 2021
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Influence-guided Data Augmentation for Neural Tensor Completion Sejoon Oh Sungchul Kim Ryan A. Rossi Srijan Kumar 28 10 0 23 Aug 2021
Data Pricing in Machine Learning Pipelines Zicun Cong Xuan Luo J. Pei Feida Zhu Yong Zhang 28 46 0 18 Aug 2021
Unified Regularity Measures for Sample-wise Learning and Generalization Chi Zhang Xiaoning Ma Yu Liu Le Wang Yuanqi Su Yuehu Liu 39 1 0 09 Aug 2021
Semi-Supervised Active Learning with Temporal Output Discrepancy Siyu Huang Tianyang Wang Haoyi Xiong Jun Huan Dejing Dou UQCV 30 66 0 29 Jul 2021
Explainable artificial intelligence (XAI) in deep learning-based medical image analysis Bas H. M. van der Velden Hugo J. Kuijf K. Gilhuijs M. Viergever XAI 45 640 0 22 Jul 2021
CHEF: A Cheap and Fast Pipeline for Iteratively Cleaning Label Uncertainties (Technical Report) Yinjun Wu James Weimer S. Davidson 23 4 0 19 Jul 2021
M2Lens: Visualizing and Explaining Multimodal Models for Sentiment Analysis Xingbo Wang Jianben He Zhihua Jin Muqiao Yang Yong Wang Huamin Qu 24 75 0 17 Jul 2021
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Survey: Leakage and Privacy at Inference Time Marija Jegorova Chaitanya Kaul Charlie Mayor Alison Q. OÑeil Alexander Weir Roderick Murray-Smith Sotirios A. Tsaftaris PILM MIACV 33 71 0 04 Jul 2021
Demystifying statistical learning based on efficient influence functions Oliver Hines O. Dukes Karla Diaz-Ordaz S. Vansteelandt TDI 32 110 0 01 Jul 2021
Combining Feature and Instance Attribution to Detect Artifacts Pouya Pezeshkpour Sarthak Jain Sameer Singh Byron C. Wallace TDI 23 43 0 01 Jul 2021
The Threat of Offensive AI to Organizations Yisroel Mirsky Ambra Demontis J. Kotak Ram Shankar Deng Gelei Liu Yang Xinming Zhang Wenke Lee Yuval Elovici Battista Biggio 38 81 0 30 Jun 2021
Certifiable Machine Unlearning for Linear Models Ananth Mahadevan M. Mathioudakis MU 14 45 0 29 Jun 2021
Towards Automated Evaluation of Explanations in Graph Neural Networks Bannihati Kumar Vanya Balaji Ganesan Aniket Saxena Devbrat Sharma Arvind Agarwal XAI GNN 29 4 0 22 Jun 2021
Adversarial Examples Make Strong Poisons Liam H. Fowl Micah Goldblum Ping Yeh-Chiang Jonas Geiping Wojtek Czaja Tom Goldstein SILM 37 132 0 21 Jun 2021
Accumulative Poisoning Attacks on Real-time Data Tianyu Pang Xiao Yang Yinpeng Dong Hang Su Jun Zhu 37 20 0 18 Jun 2021
Poisoning and Backdooring Contrastive Learning Nicholas Carlini Andreas Terzis 46 158 0 17 Jun 2021
Certification of embedded systems based on Machine Learning: A survey Guillaume Vidot Christophe Gabreau I. Ober Iulian Ober 11 12 0 14 Jun 2021
On Sample Based Explanation Methods for NLP:Efficiency, Faithfulness, and Semantic Evaluation Wei Zhang Ziming Huang Yada Zhu Guangnan Ye Xiaodong Cui Fan Zhang 36 17 0 09 Jun 2021
On Memorization in Probabilistic Deep Generative Models G. V. D. Burg Christopher K. I. Williams TDI 25 59 0 06 Jun 2021
Defending Against Backdoor Attacks in Natural Language Generation Xiaofei Sun Xiaoya Li Yuxian Meng Xiang Ao Fei Wu Jiwei Li Tianwei Zhang AAML SILM 33 47 0 03 Jun 2021
HERALD: An Annotation Efficient Method to Detect User Disengagement in Social Conversations Weixin Liang Kai-Hui Liang Zhou Yu 45 15 0 01 Jun 2021
Evaluating the Correctness of Explainable AI Algorithms for Classification Orcun Yalcin Xiuyi Fan Siyuan Liu XAI FAtt 21 15 0 20 May 2021
A Review on Explainability in Multimodal Deep Neural Nets Gargi Joshi Rahee Walambe K. Kotecha 34 140 0 17 May 2021
A Comprehensive Taxonomy for Explainable Artificial Intelligence: A Systematic Survey of Surveys on Methods and Concepts Gesina Schwalbe Bettina Finzel XAI 34 184 0 15 May 2021
Information-theoretic Evolution of Model Agnostic Global Explanations Sukriti Verma Nikaash Puri Piyush B. Gupta Balaji Krishnamurthy FAtt 29 0 0 14 May 2021
Counterfactual Explanations for Neural Recommenders Khanh Tran Azin Ghazimatin Rishiraj Saha Roy AAML CML 60 65 0 11 May 2021
Leveraging Sparse Linear Layers for Debuggable Deep Networks Eric Wong Shibani Santurkar Aleksander Madry FAtt 22 88 0 11 May 2021
Poisoning the Unlabeled Dataset of Semi-Supervised Learning Nicholas Carlini AAML 166 68 0 04 May 2021
Explanation-Based Human Debugging of NLP Models: A Survey Piyawat Lertvittayakumjorn Francesca Toni LRM 47 79 0 30 Apr 2021
Influence Based Defense Against Data Poisoning Attacks in Online Learning Sanjay Seetharaman Shubham Malaviya KV Rosni Manish Shukla S. Lodha TDI AAML 39 9 0 24 Apr 2021
Improving Question Answering Model Robustness with Synthetic Adversarial Data Generation Max Bartolo Tristan Thrush Robin Jia Sebastian Riedel Pontus Stenetorp Douwe Kiela AAML 28 103 0 18 Apr 2021
A Backdoor Attack against 3D Point Cloud Classifiers Zhen Xiang David J. Miller Siheng Chen Xi Li G. Kesidis 3DPC AAML 38 76 0 12 Apr 2021
Rethinking the Backdoor Attacks' Triggers: A Frequency Perspective Yi Zeng Won Park Z. Morley Mao R. Jia AAML 14 210 0 07 Apr 2021
Contrastive Explanations for Explaining Model Adaptations André Artelt Fabian Hinder Valerie Vaquet Robert Feldhans Barbara Hammer 57 4 0 06 Apr 2021
Explaining the Road Not Taken Hua Shen Ting-Hao 'Kenneth' Huang FAtt XAI 37 9 0 27 Mar 2021
The Hammer and the Nut: Is Bilevel Optimization Really Needed to Poison Linear Classifiers? Antonio Emanuele Cinà Sebastiano Vascon Ambra Demontis Battista Biggio Fabio Roli Marcello Pelillo AAML 32 9 0 23 Mar 2021
Data Cleansing for Deep Neural Networks with Storage-efficient Approximation of Influence Functions Kenji Suzuki Yoshiyuki Kobayashi T. Narihira TDI 31 5 0 22 Mar 2021
Interpretable Machine Learning: Moving From Mythos to Diagnostics Valerie Chen Jeffrey Li Joon Sik Kim Gregory Plumb Ameet Talwalkar 32 29 0 10 Mar 2021
Forest Guided Smoothing I. Verdinelli Larry A. Wasserman 33 3 0 08 Mar 2021
Evaluating Robustness of Counterfactual Explanations André Artelt Valerie Vaquet Riza Velioglu Fabian Hinder Johannes Brinkrolf M. Schilling Barbara Hammer 14 46 0 03 Mar 2021
Contrastive Explanations for Model Interpretability Alon Jacovi Swabha Swayamdipta Shauli Ravfogel Yanai Elazar Yejin Choi Yoav Goldberg 49 95 0 02 Mar 2021
Efficient Client Contribution Evaluation for Horizontal Federated Learning Jie Zhao Xinghua Zhu Jianzong Wang Jing Xiao FedML 41 28 0 26 Feb 2021
Intuitively Assessing ML Model Reliability through Example-Based Explanations and Editing Model Inputs Harini Suresh Kathleen M. Lewis John Guttag Arvind Satyanarayan FAtt 45 25 0 17 Feb 2021
Connecting Interpretability and Robustness in Decision Trees through Separation Michal Moshkovitz Yao-Yuan Yang Kamalika Chaudhuri 33 22 0 14 Feb 2021
Defense Against Reward Poisoning Attacks in Reinforcement Learning Kiarash Banihashem Adish Singla Goran Radanović AAML 37 26 0 10 Feb 2021
Explaining Inference Queries with Bayesian Optimization Brandon Lockhart Jinglin Peng Weiyuan Wu Jiannan Wang Eugene Wu 26 7 0 10 Feb 2021