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
Input Similarity from the Neural Network Perspective Guillaume Charpiat N. Girard Loris Felardos Y. Tarabalka 32 68 0 10 Feb 2021
Mitigating belief projection in explainable artificial intelligence via Bayesian Teaching Scott Cheng-Hsin Yang Wai Keen Vong Ravi B. Sojitra Tomas Folke Patrick Shafto 24 42 0 07 Feb 2021
Influence Estimation for Generative Adversarial Networks Naoyuki Terashita Hiroki Ohashi Yuichi Nonaka T. Kanemaru TDI 38 12 0 20 Jan 2021
Dissonance Between Human and Machine Understanding Zijian Zhang Jaspreet Singh U. Gadiraju Avishek Anand 59 74 0 18 Jan 2021
Estimating informativeness of samples with Smooth Unique Information Hrayr Harutyunyan Alessandro Achille Giovanni Paolini Orchid Majumder Avinash Ravichandran Rahul Bhotika Stefano Soatto 27 25 0 17 Jan 2021
Bayesian Inference Forgetting Shaopeng Fu Fengxiang He Yue Xu Dacheng Tao MU 28 12 0 16 Jan 2021
Unlearnable Examples: Making Personal Data Unexploitable Hanxun Huang Xingjun Ma S. Erfani James Bailey Yisen Wang MIACV 156 190 0 13 Jan 2021
Explain and Predict, and then Predict Again Zijian Zhang Koustav Rudra Avishek Anand FAtt 33 51 0 11 Jan 2021
FastIF: Scalable Influence Functions for Efficient Model Interpretation and Debugging Han Guo Nazneen Rajani Peter Hase Joey Tianyi Zhou Caiming Xiong TDI 46 102 0 31 Dec 2020
Coded Machine Unlearning Nasser Aldaghri Hessam Mahdavifar Ahmad Beirami MIACV 27 38 0 31 Dec 2020
Mixed-Privacy Forgetting in Deep Networks Aditya Golatkar Alessandro Achille Avinash Ravichandran M. Polito Stefano Soatto CLL MU 130 161 0 24 Dec 2020
LQF: Linear Quadratic Fine-Tuning Alessandro Achille Aditya Golatkar Avinash Ravichandran M. Polito Stefano Soatto 31 27 0 21 Dec 2020
Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses Micah Goldblum Dimitris Tsipras Chulin Xie Xinyun Chen Avi Schwarzschild D. Song Aleksander Madry Bo Li Tom Goldstein SILM 34 271 0 18 Dec 2020
Exacerbating Algorithmic Bias through Fairness Attacks Ninareh Mehrabi Muhammad Naveed Fred Morstatter Aram Galstyan AAML 33 67 0 16 Dec 2020
Are We Ready For Learned Cardinality Estimation? Xiaoying Wang Changbo Qu Weiyuan Wu Jiannan Wang Qingqing Zhou 39 113 0 12 Dec 2020
Data Appraisal Without Data Sharing Mimee Xu Laurens van der Maaten Awni Y. Hannun TDI 39 6 0 11 Dec 2020
Efficient Estimation of Influence of a Training Instance Sosuke Kobayashi Sho Yokoi Jun Suzuki Kentaro Inui TDI 37 15 0 08 Dec 2020
Privacy and Robustness in Federated Learning: Attacks and Defenses Lingjuan Lyu Han Yu Xingjun Ma Chen Chen Lichao Sun Jun Zhao Qiang Yang Philip S. Yu FedML 183 357 0 07 Dec 2020
Self-Explaining Structures Improve NLP Models Zijun Sun Chun Fan Qinghong Han Xiaofei Sun Yuxian Meng Fei Wu Jiwei Li MILM XAI LRM FAtt 46 38 0 03 Dec 2020
Cross-Loss Influence Functions to Explain Deep Network Representations Andrew Silva Rohit Chopra Matthew C. Gombolay TDI 26 15 0 03 Dec 2020
How Robust are Randomized Smoothing based Defenses to Data Poisoning? Akshay Mehra B. Kailkhura Pin-Yu Chen Jihun Hamm OOD AAML 28 32 0 02 Dec 2020
Why model why? Assessing the strengths and limitations of LIME Jurgen Dieber S. Kirrane FAtt 26 97 0 30 Nov 2020
Objective Diagnosis for Histopathological Images Based on Machine Learning Techniques: Classical Approaches and New Trends Naira Elazab Hassan H. Soliman Shaker El-Sappagh S. Islam Mohammed M Elmogy 17 20 0 10 Nov 2020
Dataset Meta-Learning from Kernel Ridge-Regression Timothy Nguyen Zhourung Chen Jaehoon Lee DD 36 241 0 30 Oct 2020
Concealed Data Poisoning Attacks on NLP Models Eric Wallace Tony Zhao Shi Feng Sameer Singh SILM 29 18 0 23 Oct 2020
Axiom Learning and Belief Tracing for Transparent Decision Making in Robotics Tiago Mota Mohan Sridharan 21 5 0 20 Oct 2020
Mitigating Sybil Attacks on Differential Privacy based Federated Learning Yupeng Jiang Yong Li Yipeng Zhou Xi Zheng FedML AAML 29 15 0 20 Oct 2020
Interpretable Machine Learning -- A Brief History, State-of-the-Art and Challenges Christoph Molnar Giuseppe Casalicchio B. Bischl AI4TS AI4CE 28 396 0 19 Oct 2020
Poison Attacks against Text Datasets with Conditional Adversarially Regularized Autoencoder Alvin Chan Yi Tay Yew-Soon Ong Aston Zhang SILM 23 56 0 06 Oct 2020
Explaining Deep Neural Networks Oana-Maria Camburu XAI FAtt 38 26 0 04 Oct 2020
RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language Models Samuel Gehman Suchin Gururangan Maarten Sap Yejin Choi Noah A. Smith 83 1,134 0 24 Sep 2020
Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics Swabha Swayamdipta Roy Schwartz Nicholas Lourie Yizhong Wang Hannaneh Hajishirzi Noah A. Smith Yejin Choi 54 429 0 22 Sep 2020
Beyond Individualized Recourse: Interpretable and Interactive Summaries of Actionable Recourses Kaivalya Rawal Himabindu Lakkaraju 27 11 0 15 Sep 2020
Machine Unlearning for Random Forests Jonathan Brophy Daniel Lowd MU 24 159 0 11 Sep 2020
Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching Jonas Geiping Liam H. Fowl Wenjie Huang W. Czaja Gavin Taylor Michael Moeller Tom Goldstein AAML 21 215 0 04 Sep 2020
Interactive Visual Study of Multiple Attributes Learning Model of X-Ray Scattering Images Xinyi Huang Suphanut Jamonnak Ye Zhao Boyu Wang Minh Hoai Kevin Yager Wei Xu 30 5 0 03 Sep 2020
Stochastic Optimization Forests Nathan Kallus Xiaojie Mao 32 48 0 17 Aug 2020
Survey of XAI in digital pathology Milda Pocevičiūtė Gabriel Eilertsen Claes Lundström 14 56 0 14 Aug 2020
Reliable Post hoc Explanations: Modeling Uncertainty in Explainability Dylan Slack Sophie Hilgard Sameer Singh Himabindu Lakkaraju FAtt 29 162 0 11 Aug 2020
What Neural Networks Memorize and Why: Discovering the Long Tail via Influence Estimation Vitaly Feldman Chiyuan Zhang TDI 46 443 0 09 Aug 2020
MetAL: Active Semi-Supervised Learning on Graphs via Meta Learning Kaushalya Madhawa T. Murata AI4CE 35 8 0 22 Jul 2020
Sequential Explanations with Mental Model-Based Policies A. Yeung Shalmali Joshi Joseph Jay Williams Frank Rudzicz FAtt LRM 36 15 0 17 Jul 2020
Do Adversarially Robust ImageNet Models Transfer Better? Hadi Salman Andrew Ilyas Logan Engstrom Ashish Kapoor Aleksander Madry 37 419 0 16 Jul 2020
Monitoring and explainability of models in production Janis Klaise A. V. Looveren Clive Cox G. Vacanti Alexandru Coca 43 49 0 13 Jul 2020
Quality Inference in Federated Learning with Secure Aggregation Balázs Pejó G. Biczók FedML 23 22 0 13 Jul 2020
Understanding Adversarial Examples from the Mutual Influence of Images and Perturbations Chaoning Zhang Philipp Benz Tooba Imtiaz In-So Kweon SSL AAML 22 118 0 13 Jul 2020
Reflection Backdoor: A Natural Backdoor Attack on Deep Neural Networks Yunfei Liu Xingjun Ma James Bailey Feng Lu AAML 22 505 0 05 Jul 2020
Efficient computation and analysis of distributional Shapley values Yongchan Kwon Manuel A. Rivas James Zou FAtt TDI 24 61 0 02 Jul 2020
Not All Unlabeled Data are Equal: Learning to Weight Data in Semi-supervised Learning Zhongzheng Ren Raymond A. Yeh Alex Schwing 46 95 0 02 Jul 2020
Unifying Model Explainability and Robustness via Machine-Checkable Concepts Vedant Nanda Till Speicher John P. Dickerson Krishna P. Gummadi Muhammad Bilal Zafar AAML 14 4 0 01 Jul 2020