Understanding Black-box Predictions via Influence Functions

14 March 2017

Pang Wei Koh

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

29 / 79 papers shown

Title
On the Proactive Generation of Unsafe Images From Text-To-Image Models Using Benign Prompts Yixin Wu Ning Yu Michael Backes Yun Shen Yang Zhang DiffM 76 8 0 25 Oct 2023
Adapt then Unlearn: Exploring Parameter Space Semantics for Unlearning in Generative Adversarial Networks Piyush Tiwary Atri Guha Subhodip Panda Prathosh A.P. MU GAN 72 8 0 25 Sep 2023
Unveiling the frontiers of deep learning: innovations shaping diverse domains Shams Forruque Ahmed Md. Sakib Bin Alam Maliha Kabir Shaila Afrin Sabiha Jannat Rafa Aanushka Mehjabin Amir H. Gandomi AI4CE 60 2 0 06 Sep 2023
Addressing Selection Bias in Computerized Adaptive Testing: A User-Wise Aggregate Influence Function Approach Soonwoo Kwon Sojung Kim S. Lee Jin-Young Kim Suyeong An Kyuseok Kim 30 3 0 23 Aug 2023
Verifiable and Provably Secure Machine Unlearning Thorsten Eisenhofer Doreen Riepel Varun Chandrasekaran Esha Ghosh O. Ohrimenko Nicolas Papernot AAML MU 56 26 0 17 Oct 2022
Energy-Latency Attacks via Sponge Poisoning Antonio Emanuele Cinà Ambra Demontis Battista Biggio Fabio Roli Marcello Pelillo SILM 84 29 0 14 Mar 2022
What Neural Networks Memorize and Why: Discovering the Long Tail via Influence Estimation Vitaly Feldman Chiyuan Zhang TDI 83 452 0 09 Aug 2020
Towards Probabilistic Verification of Machine Unlearning David M. Sommer Liwei Song Sameer Wagh Prateek Mittal AAML 64 71 0 09 Mar 2020
Penalty Method for Inversion-Free Deep Bilevel Optimization Akshay Mehra Jihun Hamm 44 46 0 08 Nov 2019
Architecture Selection via the Trade-off Between Accuracy and Robustness Zhun Deng Cynthia Dwork Jialiang Wang Yao-Min Zhao AAML 42 3 0 04 Jun 2019
Understanding Neural Networks through Representation Erasure Jiwei Li Will Monroe Dan Jurafsky AAML MILM 62 562 0 24 Dec 2016
"Influence Sketching": Finding Influential Samples In Large-Scale Regressions M. Wojnowicz Ben Cruz Xuan Zhao Brian Wallace Matt Wolff Jay Luan Caleb Crable TDI 32 30 0 17 Nov 2016
Data Poisoning Attacks on Factorization-Based Collaborative Filtering Bo Li Yining Wang Aarti Singh Yevgeniy Vorobeychik AAML 53 341 0 29 Aug 2016
European Union regulations on algorithmic decision-making and a "right to explanation" B. Goodman Seth Flaxman FaML AILaw 52 1,888 0 28 Jun 2016
Theano: A Python framework for fast computation of mathematical expressions The Theano Development Team Rami Al-Rfou Guillaume Alain Amjad Almahairi Christof Angermüller ... Kelvin Xu Lijun Xue Li Yao Saizheng Zhang Ying Zhang 112 2,338 0 09 May 2016
Not Just a Black Box: Learning Important Features Through Propagating Activation Differences Avanti Shrikumar Peyton Greenside A. Shcherbina A. Kundaje FAtt 40 782 0 05 May 2016
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems Martín Abadi Ashish Agarwal P. Barham E. Brevdo Zhiwen Chen ... Pete Warden Martin Wattenberg Martin Wicke Yuan Yu Xiaoqiang Zheng 158 11,135 0 14 Mar 2016
Auditing Black-box Models for Indirect Influence Philip Adler Casey Falk Sorelle A. Friedler Gabriel Rybeck C. Scheidegger Brandon Smith Suresh Venkatasubramanian TDI MLAU 77 288 0 23 Feb 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 420 16,765 0 16 Feb 2016
Second-Order Stochastic Optimization for Machine Learning in Linear Time Naman Agarwal Brian Bullins Elad Hazan ODL 28 102 0 12 Feb 2016
Rethinking the Inception Architecture for Computer Vision Christian Szegedy Vincent Vanhoucke Sergey Ioffe Jonathon Shlens Z. Wojna 3DV BDL 395 27,231 0 02 Dec 2015
DeepFool: a simple and accurate method to fool deep neural networks Seyed-Mohsen Moosavi-Dezfooli Alhussein Fawzi P. Frossard AAML 87 4,878 0 14 Nov 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 588 149,474 0 22 Dec 2014
Striving for Simplicity: The All Convolutional Net Jost Tobias Springenberg Alexey Dosovitskiy Thomas Brox Martin Riedmiller FAtt 144 4,653 0 21 Dec 2014
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 143 18,922 0 20 Dec 2014
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 914 39,383 0 01 Sep 2014
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps Karen Simonyan Andrea Vedaldi Andrew Zisserman FAtt 128 7,252 0 20 Dec 2013
DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition Jeff Donahue Yangqing Jia Oriol Vinyals Judy Hoffman Ning Zhang Eric Tzeng Trevor Darrell VLM ObjD 128 4,946 0 06 Oct 2013
Poisoning Attacks against Support Vector Machines Battista Biggio B. Nelson Pavel Laskov AAML 63 1,580 0 27 Jun 2012