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
Discriminative Jackknife: Quantifying Uncertainty in Deep Learning via Higher-Order Influence Functions Ahmed Alaa M. Schaar UD UQCV BDL TDI 29 53 0 29 Jun 2020
BERTology Meets Biology: Interpreting Attention in Protein Language Models Jesse Vig Ali Madani Lav Varshney Caiming Xiong R. Socher Nazneen Rajani 34 289 0 26 Jun 2020
Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance Gagan Bansal Tongshuang Wu Joyce Zhou Raymond Fok Besmira Nushi Ece Kamar Marco Tulio Ribeiro Daniel S. Weld 42 584 0 26 Jun 2020
DeltaGrad: Rapid retraining of machine learning models Yinjun Wu Yan Sun S. Davidson MU 27 197 0 26 Jun 2020
Influence Functions in Deep Learning Are Fragile S. Basu Phillip E. Pope S. Feizi TDI 37 220 0 25 Jun 2020
Subpopulation Data Poisoning Attacks Matthew Jagielski Giorgio Severi Niklas Pousette Harger Alina Oprea AAML SILM 24 114 0 24 Jun 2020
Generative causal explanations of black-box classifiers Matthew R. O’Shaughnessy Gregory H. Canal Marissa Connor Mark A. Davenport Christopher Rozell CML 35 73 0 24 Jun 2020
Approximate Cross-Validation for Structured Models S. Ghosh William T. Stephenson Tin D. Nguyen Sameer K. Deshpande Tamara Broderick 18 15 0 23 Jun 2020
Just How Toxic is Data Poisoning? A Unified Benchmark for Backdoor and Data Poisoning Attacks Avi Schwarzschild Micah Goldblum Arjun Gupta John P. Dickerson Tom Goldstein AAML TDI 21 162 0 22 Jun 2020
Frequentist Uncertainty in Recurrent Neural Networks via Blockwise Influence Functions Ahmed Alaa M. Schaar UQCV BDL 14 22 0 20 Jun 2020
Meta Approach to Data Augmentation Optimization Ryuichiro Hataya Jan Zdenek Kazuki Yoshizoe Hideki Nakayama 32 34 0 14 Jun 2020
Dataset Condensation with Gradient Matching Bo Zhao Konda Reddy Mopuri Hakan Bilen DD 41 479 0 10 Jun 2020
Coresets via Bilevel Optimization for Continual Learning and Streaming Zalan Borsos Mojmír Mutný Andreas Krause CLL 38 227 0 06 Jun 2020
Interpretable Time-series Classification on Few-shot Samples Wensi Tang Lu Liu Guodong Long AI4TS 8 20 0 03 Jun 2020
Explaining Black Box Predictions and Unveiling Data Artifacts through Influence Functions Xiaochuang Han Byron C. Wallace Yulia Tsvetkov MILM FAtt AAML TDI 28 165 0 14 May 2020
Ensembled sparse-input hierarchical networks for high-dimensional datasets Jean Feng N. Simon 19 4 0 11 May 2020
Towards Frequency-Based Explanation for Robust CNN Zifan Wang Yilin Yang Ankit Shrivastava Varun Rawal Zihao Ding AAML FAtt 21 47 0 06 May 2020
Explainable Deep Learning: A Field Guide for the Uninitiated Gabrielle Ras Ning Xie Marcel van Gerven Derek Doran AAML XAI 49 371 0 30 Apr 2020
Time Series Forecasting With Deep Learning: A Survey Bryan Lim S. Zohren AI4TS AI4CE 59 1,192 0 28 Apr 2020
Generative Data Augmentation for Commonsense Reasoning Yiben Yang Chaitanya Malaviya Jared Fernandez Swabha Swayamdipta Ronan Le Bras Ji-ping Wang Chandra Bhagavatula Yejin Choi Doug Downey LRM 30 91 0 24 Apr 2020
Adversarial Attacks and Defenses: An Interpretation Perspective Ninghao Liu Mengnan Du Ruocheng Guo Huan Liu Xia Hu AAML 31 8 0 23 Apr 2020
Complaint-driven Training Data Debugging for Query 2.0 Weiyuan Wu Lampros Flokas Eugene Wu Jiannan Wang 32 43 0 12 Apr 2020
RelatIF: Identifying Explanatory Training Examples via Relative Influence Elnaz Barshan Marc-Etienne Brunet Gintare Karolina Dziugaite TDI 47 30 0 25 Mar 2020
Towards Probabilistic Verification of Machine Unlearning David M. Sommer Liwei Song Sameer Wagh Prateek Mittal AAML 13 71 0 09 Mar 2020
Causal Interpretability for Machine Learning -- Problems, Methods and Evaluation Raha Moraffah Mansooreh Karami Ruocheng Guo A. Raglin Huan Liu CML ELM XAI 32 213 0 09 Mar 2020
Forgetting Outside the Box: Scrubbing Deep Networks of Information Accessible from Input-Output Observations Aditya Golatkar Alessandro Achille Stefano Soatto MU OOD 33 189 0 05 Mar 2020
Regularisation Can Mitigate Poisoning Attacks: A Novel Analysis Based on Multiobjective Bilevel Optimisation Javier Carnerero-Cano Luis Muñoz-González P. Spencer Emil C. Lupu AAML 36 11 0 28 Feb 2020
Approximate Data Deletion from Machine Learning Models Zachary Izzo Mary Anne Smart Kamalika Chaudhuri James Zou MU 22 251 0 24 Feb 2020
Data Heterogeneity Differential Privacy: From Theory to Algorithm Yilin Kang Jian Li Yong Liu Weiping Wang 33 1 0 20 Feb 2020
Unifying Graph Convolutional Neural Networks and Label Propagation Hongwei Wang J. Leskovec GNN 30 166 0 17 Feb 2020
Convex Density Constraints for Computing Plausible Counterfactual Explanations André Artelt Barbara Hammer 19 47 0 12 Feb 2020
Decisions, Counterfactual Explanations and Strategic Behavior Stratis Tsirtsis Manuel Gomez Rodriguez 27 58 0 11 Feb 2020
Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions Omer Gottesman Joseph D. Futoma Yao Liu Soanli Parbhoo Leo Anthony Celi Emma Brunskill Finale Doshi-Velez OffRL 147 56 0 10 Feb 2020
Machine Unlearning: Linear Filtration for Logit-based Classifiers Thomas Baumhauer Pascal Schöttle Matthias Zeppelzauer MU 114 130 0 07 Feb 2020
GraphLIME: Local Interpretable Model Explanations for Graph Neural Networks Q. Huang M. Yamada Yuan Tian Dinesh Singh Dawei Yin Yi-Ju Chang FAtt 37 346 0 17 Jan 2020
Keeping Community in the Loop: Understanding Wikipedia Stakeholder Values for Machine Learning-Based Systems C. E. Smith Bowen Yu Anjali Srivastava Aaron L Halfaker Loren G. Terveen Haiyi Zhu KELM 21 69 0 14 Jan 2020
Multi-Source Domain Adaptation for Text Classification via DistanceNet-Bandits Han Guo Ramakanth Pasunuru Joey Tianyi Zhou 30 114 0 13 Jan 2020
Learning to Multi-Task Learn for Better Neural Machine Translation Poorya Zaremoodi Gholamreza Haffari 29 3 0 10 Jan 2020
On Interpretability of Artificial Neural Networks: A Survey Fenglei Fan Jinjun Xiong Mengzhou Li Ge Wang AAML AI4CE 43 301 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
Explainability Fact Sheets: A Framework for Systematic Assessment of Explainable Approaches Kacper Sokol Peter A. Flach XAI 19 299 0 11 Dec 2019
Machine Unlearning Lucas Bourtoule Varun Chandrasekaran Christopher A. Choquette-Choo Hengrui Jia Adelin Travers Baiwu Zhang David Lie Nicolas Papernot MU 65 818 0 09 Dec 2019
Label-Consistent Backdoor Attacks Alexander Turner Dimitris Tsipras Aleksander Madry AAML 11 383 0 05 Dec 2019
Less Is Better: Unweighted Data Subsampling via Influence Function Zifeng Wang Hong Zhu Zhenhua Dong Xiuqiang He Shao-Lun Huang TDI 34 51 0 03 Dec 2019
Automated Dependence Plots David I. Inouye Liu Leqi Joon Sik Kim Bryon Aragam Pradeep Ravikumar 12 1 0 02 Dec 2019
Revealing Perceptible Backdoors, without the Training Set, via the Maximum Achievable Misclassification Fraction Statistic Zhen Xiang David J. Miller Hang Wang G. Kesidis AAML 34 9 0 18 Nov 2019
Multi-modal Deep Guided Filtering for Comprehensible Medical Image Processing Bernhard Stimpel Christopher Syben Franziska Schirrmacher P. Hoelter Arnd Dörfler Andreas Maier MedIm 24 23 0 18 Nov 2019
An explanation method for Siamese neural networks Lev V. Utkin M. Kovalev E. Kasimov 27 14 0 18 Nov 2019
REFIT: A Unified Watermark Removal Framework For Deep Learning Systems With Limited Data Xinyun Chen Wenxiao Wang Chris Bender Yiming Ding R. Jia Bo Li D. Song AAML 27 107 0 17 Nov 2019
On the computation of counterfactual explanations -- A survey André Artelt Barbara Hammer LRM 30 50 0 15 Nov 2019