Chen Zhu
Freelb: Enhanced adversarial training for natural language understanding
C Zhu, Y Cheng, Z Gan, S Sun, T Goldstein, J Liu
ICLR 2020 & arXiv:1909.11764, 2019
Structured attentions for visual question answering
C Zhu, Y Zhao, S Huang, K Tu, Y Ma
ICCV 2017 & arXiv: 1708.02071, 2017
Compressing neural networks using the variational information bottleneck
B Dai, C Zhu, D Wipf
ICML 2018 & arXiv: 1802.10399, 2018
Transferable Clean-Label Poisoning Attacks on Deep Neural Nets
C Zhu, WR Huang, A Shafahi, H Li, G Taylor, C Studer, T Goldstein
ICML 2019 & arXiv: 1905.05897, 2019
Large-Scale Adversarial Training for Vision-and-Language Representation Learning
Z Gan, YC Chen, L Li, C Zhu, Y Cheng, J Liu
NeurIPS 2020 & arXiv:2006.06195, 2020
Learning visual knowledge memory networks for visual question answering
Z Su, C Zhu, Y Dong, D Cai, Y Chen, J Li
CVPR 2018 & arXiv: 1806.04860, 2018
Certified defenses for adversarial patches
PY Chiang, R Ni, A Abdelkader, C Zhu, C Studor, T Goldstein
ICLR 2020 & arXiv:2003.06693, 2020
Fine-grained video categorization with redundancy reduction attention
C Zhu, X Tan, F Zhou, X Liu, K Yue, E Ding, Y Ma
Proceedings of the European Conference on Computer Vision (ECCV), 136-152, 2018
Adversarially robust transfer learning
A Shafahi, P Saadatpanah, C Zhu, A Ghiasi, C Studer, D Jacobs, ...
ICLR 2020 & arXiv:1905.08232, 2019
Learning from Noisy Anchors for One-stage Object Detection
H Li, Z Wu, C Zhu, C Xiong, R Socher, LS Davis
CVPR 2020 & arXiv:1912.05086, 2019
Robust plane-based calibration of multiple non-overlapping cameras
C Zhu, Z Zhou, Z Xing, Y Dong, Y Ma, J Yu
2016 Fourth International Conference on 3D Vision (3DV), 658-666, 2016
Deep k-NN Defense Against Clean-Label Data Poisoning Attacks
N Peri, N Gupta, WR Huang, L Fowl, C Zhu, S Feizi, T Goldstein, ...
European Conference on Computer Vision, 55-70, 2020
Flag: Adversarial data augmentation for graph neural networks
K Kong, G Li, M Ding, Z Wu, C Zhu, B Ghanem, G Taylor, T Goldstein
arXiv preprint arXiv:2010.09891, 2020
GradInit: Learning to initialize neural networks for stable and efficient training
C Zhu, R Ni, Z Xu, K Kong, WR Huang, T Goldstein
arXiv preprint arXiv:2102.08098, 2021
Improving the tightness of convex relaxation bounds for training certifiably robust classifiers
C Zhu, R Ni, P Chiang, H Li, F Huang, T Goldstein
arXiv preprint arXiv:2002.09766, 2020
Modifying Memories in Transformer Models
C Zhu, AS Rawat, M Zaheer, S Bhojanapalli, D Li, F Yu, S Kumar
arXiv preprint arXiv:2012.00363, 2020
Are Adversarial Examples Created Equal? A Learnable Weighted Minimax Risk for Robustness under Non-uniform Attacks
H Zeng, C Zhu, T Goldstein, F Huang
AAAI 2021 & arXiv:2010.12989, 2020
Headless Horseman: Adversarial Attacks on Transfer Learning Models
A Abdelkader, MJ Curry, L Fowl, T Goldstein, A Schwarzschild, M Shu, ...
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
The Intrinsic Dimension of Images and Its Impact on Learning
P Pope, C Zhu, A Abdelkader, M Goldblum, T Goldstein
ICLR 2021 & arXiv:2104.08894, 2021
Towards Accurate Quantization and Pruning via Data-free Knowledge Transfer
C Zhu, Z Xu, A Shafahi, M Shu, A Ghiasi, T Goldstein
arXiv preprint arXiv:2010.07334, 2020
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