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Chen Zhu
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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
4092020
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, 2020
3962020
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
2712019
Compressing neural networks using the variational information bottleneck
B Dai, C Zhu, B Guo, D Wipf
ICML 2018 & arXiv: 1802.10399, 2018
1722018
A field guide to federated optimization
J Wang, Z Charles, Z Xu, G Joshi, HB McMahan, M Al-Shedivat, G Andrew, ...
arXiv preprint arXiv:2107.06917, 2021
1552021
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
1492021
Robust optimization as data augmentation for large-scale graphs
K Kong, G Li, M Ding, Z Wu, C Zhu, B Ghanem, G Taylor, T Goldstein
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
144*2022
Certified defenses for adversarial patches
PY Chiang, R Ni, A Abdelkader, C Zhu, C Studor, T Goldstein
ICLR 2020 & arXiv:2003.06693, 2020
1422020
Adversarially robust transfer learning
A Shafahi, P Saadatpanah, C Zhu, A Ghiasi, C Studer, D Jacobs, ...
ICLR 2020 & arXiv:1905.08232, 2019
1242019
Structured attentions for visual question answering
C Zhu, Y Zhao, S Huang, K Tu, Y Ma
ICCV 2017 & arXiv: 1708.02071, 2017
1132017
Deep k-NN Defense Against Clean-Label Data Poisoning Attacks
N Peri, N Gupta, WR Huang, L Fowl, C Zhu, S Feizi, T Goldstein, ...
Computer Vision–ECCV 2020 Workshops: Glasgow, UK, August 23–28, 2020 …, 2020
1032020
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
902019
Long-short transformer: Efficient transformers for language and vision
C Zhu, W Ping, C Xiao, M Shoeybi, T Goldstein, A Anandkumar, ...
NeurIPS 2021 & arXiv:2107.02192, 2021
832021
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
762018
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
542020
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
532018
GradInit: Learning to initialize neural networks for stable and efficient training
C Zhu, R Ni, Z Xu, K Kong, WR Huang, T Goldstein
NeurIPS 2021 & arXiv:2102.08098, 2021
442021
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
192020
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
192016
Diurnal or Nocturnal? Federated Learning of Multi-branch Networks from Periodically Shifting Distributions
C Zhu, Z Xu, M Chen, J Konečnư, A Hard, T Goldstein
ICLR 2022 & NeurIPS 2021 Workshop on Distribution Shifts, 2022
162022
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