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DARTS for Inverse Problems: a Study on Hyperparameter Sensitivity


Aug 12, 2021
Jonas Geiping, Jovita Lukasik, Margret Keuper, Michael Moeller

* 11 pages, 5 figures 

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Adversarial Examples Make Strong Poisons


Jun 21, 2021
Liam Fowl, Micah Goldblum, Ping-yeh Chiang, Jonas Geiping, Wojtek Czaja, Tom Goldstein


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Training or Architecture? How to Incorporate Invariance in Neural Networks


Jun 18, 2021
Kanchana Vaishnavi Gandikota, Jonas Geiping, Zorah Lähner, Adam Czapliński, Michael Moeller


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Preventing Unauthorized Use of Proprietary Data: Poisoning for Secure Dataset Release


Mar 05, 2021
Liam Fowl, Ping-yeh Chiang, Micah Goldblum, Jonas Geiping, Arpit Bansal, Wojtek Czaja, Tom Goldstein


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DP-InstaHide: Provably Defusing Poisoning and Backdoor Attacks with Differentially Private Data Augmentations


Mar 02, 2021
Eitan Borgnia, Jonas Geiping, Valeriia Cherepanova, Liam Fowl, Arjun Gupta, Amin Ghiasi, Furong Huang, Micah Goldblum, Tom Goldstein

* 11 pages, 5 figures 

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What Doesn't Kill You Makes You Robust(er): Adversarial Training against Poisons and Backdoors


Feb 26, 2021
Jonas Geiping, Liam Fowl, Gowthami Somepalli, Micah Goldblum, Michael Moeller, Tom Goldstein

* 17 pages, 14 figures 

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Strong Data Augmentation Sanitizes Poisoning and Backdoor Attacks Without an Accuracy Tradeoff


Nov 18, 2020
Eitan Borgnia, Valeriia Cherepanova, Liam Fowl, Amin Ghiasi, Jonas Geiping, Micah Goldblum, Tom Goldstein, Arjun Gupta

* Authors ordered alphabetically 

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Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching


Sep 04, 2020
Jonas Geiping, Liam Fowl, W. Ronny Huang, Wojciech Czaja, Gavin Taylor, Michael Moeller, Tom Goldstein

* First two authors contributed equally. Last two authors contributed equally. 21 pages, 11 figures 

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Fast Convex Relaxations using Graph Discretizations


Apr 23, 2020
Jonas Geiping, Fjedor Gaede, Hartmut Bauermeister, Michael Moeller

* 19 pages, 10 figures 

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MetaPoison: Practical General-purpose Clean-label Data Poisoning


Apr 01, 2020
W. Ronny Huang, Jonas Geiping, Liam Fowl, Gavin Taylor, Tom Goldstein

* First two authors contributed equally 

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Inverting Gradients -- How easy is it to break privacy in federated learning?


Mar 31, 2020
Jonas Geiping, Hartmut Bauermeister, Hannah Dröge, Michael Moeller

* 26 pages, 17 figures. The first three authors contributed equally 

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WITCHcraft: Efficient PGD attacks with random step size


Nov 18, 2019
Ping-Yeh Chiang, Jonas Geiping, Micah Goldblum, Tom Goldstein, Renkun Ni, Steven Reich, Ali Shafahi

* Authors contributed equally and are listed in alphabetical order 

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Truth or Backpropaganda? An Empirical Investigation of Deep Learning Theory


Oct 01, 2019
Micah Goldblum, Jonas Geiping, Avi Schwarzschild, Michael Moeller, Tom Goldstein

* 16 pages, 5 figures. First two authors contributed equally 

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Parametric Majorization for Data-Driven Energy Minimization Methods


Aug 17, 2019
Jonas Geiping, Michael Moeller

* 16 pages, 5 figures, accepted for ICCV 2019 

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Composite Optimization by Nonconvex Majorization-Minimization


Sep 03, 2018
Jonas Geiping, Michael Moeller

* 38 pages, 12 figures, accepted for publication in SIIMS 

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Multiframe Motion Coupling for Video Super Resolution


Dec 04, 2017
Jonas Geiping, Hendrik Dirks, Daniel Cremers, Michael Moeller


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