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An Open Review of OpenReview: A Critical Analysis of the Machine Learning Conference Review Process

Oct 26, 2020
David Tran, Alex Valtchanov, Keshav Ganapathy, Raymond Feng, Eric Slud, Micah Goldblum, Tom Goldstein

* 19 pages, 6 Figures 

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Are Adversarial Examples Created Equal? A Learnable Weighted Minimax Risk for Robustness under Non-uniform Attacks

Oct 24, 2020
Huimin Zeng, Chen Zhu, Tom Goldstein, Furong Huang


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FLAG: Adversarial Data Augmentation for Graph Neural Networks

Oct 19, 2020
Kezhi Kong, Guohao Li, Mucong Ding, Zuxuan Wu, Chen Zhu, Bernard Ghanem, Gavin Taylor, Tom Goldstein


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Towards Accurate Quantization and Pruning via Data-free Knowledge Transfer

Oct 14, 2020
Chen Zhu, Zheng Xu, Ali Shafahi, Manli Shu, Amin Ghiasi, Tom Goldstein


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Data Augmentation for Meta-Learning

Oct 14, 2020
Renkun Ni, Micah Goldblum, Amr Sharaf, Kezhi Kong, Tom Goldstein


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Random Network Distillation as a Diversity Metric for Both Image and Text Generation

Oct 13, 2020
Liam Fowl, Micah Goldblum, Arjun Gupta, Amr Sharaf, Tom Goldstein


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ProportionNet: Balancing Fairness and Revenue for Auction Design with Deep Learning

Oct 13, 2020
Kevin Kuo, Anthony Ostuni, Elizabeth Horishny, Michael J. Curry, Samuel Dooley, Ping-yeh Chiang, Tom Goldstein, John P. Dickerson


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Prepare for the Worst: Generalizing across Domain Shifts with Adversarial Batch Normalization

Sep 21, 2020
Manli Shu, Zuxuan Wu, Micah Goldblum, Tom Goldstein


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Preparing for the Worst: Making Networks Less Brittle with Adversarial Batch Normalization

Sep 18, 2020
Manli Shu, Zuxuan Wu, Micah Goldblum, Tom Goldstein


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Certifying Confidence via Randomized Smoothing

Sep 17, 2020
Aounon Kumar, Alexander Levine, Soheil Feizi, Tom Goldstein


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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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WrapNet: Neural Net Inference with Ultra-Low-Resolution Arithmetic

Jul 26, 2020
Renkun Ni, Hong-min Chu, Oscar Castañeda, Ping-yeh Chiang, Christoph Studer, Tom Goldstein


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Detection as Regression: Certified Object Detection by Median Smoothing

Jul 07, 2020
Ping-yeh Chiang, Michael J. Curry, Ahmed Abdelkader, Aounon Kumar, John Dickerson, Tom Goldstein


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Just How Toxic is Data Poisoning? A Unified Benchmark for Backdoor and Data Poisoning Attacks

Jun 22, 2020
Avi Schwarzschild, Micah Goldblum, Arjun Gupta, John P Dickerson, Tom Goldstein

* 19 pages, 4 figures 

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Adaptive Learning Rates with Maximum Variation Averaging

Jun 21, 2020
Chen Zhu, Yu Cheng, Zhe Gan, Furong Huang, Jingjing Liu, Tom Goldstein


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Certifying Strategyproof Auction Networks

Jun 15, 2020
Michael J. Curry, Ping-Yeh Chiang, Tom Goldstein, John Dickerson


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Exploring Model Robustness with Adaptive Networks and Improved Adversarial Training

May 30, 2020
Zheng Xu, Ali Shafahi, Tom Goldstein


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Headless Horseman: Adversarial Attacks on Transfer Learning Models

Apr 20, 2020
Ahmed Abdelkader, Michael J. Curry, Liam Fowl, Tom Goldstein, Avi Schwarzschild, Manli Shu, Christoph Studer, Chen Zhu

* 5 pages, 2 figures. Accepted in ICASSP 2020. Code available on https://github.com/zhuchen03/headless-attack.git 

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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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Unraveling Meta-Learning: Understanding Feature Representations for Few-Shot Tasks

Mar 21, 2020
Micah Goldblum, Steven Reich, Liam Fowl, Renkun Ni, Valeriia Cherepanova, Tom Goldstein


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Breaking certified defenses: Semantic adversarial examples with spoofed robustness certificates

Mar 19, 2020
Amin Ghiasi, Ali Shafahi, Tom Goldstein


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Certified Defenses for Adversarial Patches

Mar 14, 2020
Ping-Yeh Chiang, Renkun Ni, Ahmed Abdelkader, Chen Zhu, Christoph Studor, Tom Goldstein

* to be published in International Conference on Learning Representations, ICLR 2020 

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Adversarial Attacks on Machine Learning Systems for High-Frequency Trading

Mar 04, 2020
Micah Goldblum, Avi Schwarzschild, Ankit B. Patel, Tom Goldstein


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Improving the Tightness of Convex Relaxation Bounds for Training Certifiably Robust Classifiers

Feb 22, 2020
Chen Zhu, Renkun Ni, Ping-yeh Chiang, Hengduo Li, Furong Huang, Tom Goldstein


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Curse of Dimensionality on Randomized Smoothing for Certifiable Robustness

Feb 08, 2020
Aounon Kumar, Alexander Levine, Tom Goldstein, Soheil Feizi


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MSE-Optimal Neural Network Initialization via Layer Fusion

Jan 28, 2020
Ramina Ghods, Andrew S. Lan, Tom Goldstein, Christoph Studer

* Extended version of the CISS 2020 paper containing the proof for convolutional layers 

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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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