Követés
Yisen Wang
Yisen Wang
Assistant Professor, Peking University
E-mail megerősítve itt: pku.edu.cn - Kezdőlap
Cím
Hivatkozott rá
Hivatkozott rá
Év
Symmetric cross entropy for robust learning with noisy labels
Y Wang, X Ma, Z Chen, Y Luo, J Yi, J Bailey
ICCV 2019, 2019
11402019
Improving Adversarial Robustness Requires Revisiting Misclassified Examples
Y Wang, D Zou, J Yi, J Bailey, X Ma, Q Gu
ICLR2020, 2020
8622020
Characterizing adversarial subspaces using local intrinsic dimensionality
X Ma, B Li, Y Wang, SM Erfani, S Wijewickrema, ME Houle, ...
ICLR2018, 2018
8622018
Adversarial Weight Perturbation Helps Robust Generalization
D Wu, S Xia, Y Wang
NeurIPS 2020, 2020
8042020
Understanding Adversarial Attacks on Deep Learning Based Medical Image Analysis Systems
X Ma, Y Niu, L Gu, Y Wang, Y Zhao, J Bailey, F Lu
Pattern Recognition, 2019
5442019
Normalized Loss Functions for Deep Learning with Noisy Labels
X Ma, H Huang, Y Wang, S Romano, S Erfani, J Bailey
ICML2020, 2020
5152020
Dimensionality-Driven Learning with Noisy Labels
X Ma*, Y Wang*, ME Houle, S Zhou, SM Erfani, ST Xia, S Wijewickrema, ...
ICML2018, 2018
4792018
On the Convergence and Robustness of Adversarial Training
Y Wang, X Ma, J Bailey, J Yi, B Zhou, Q Gu
ICML2019, 2019
4362019
Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets
D Wu, Y Wang, ST Xia, J Bailey, X Ma
ICLR2020, 2020
4012020
Iterative Learning with Open-set Noisy Labels
Y Wang, W Liu, X Ma, J Bailey, H Zha, L Song, ST Xia
CVPR2018, 2018
3802018
Adversarial Neuron Pruning Purifies Backdoored Deep Models
D Wu, Y Wang
NeurIPS 2021, 2021
3142021
Adversarial Camouflage: Hiding Physical-World Attacks with Natural Styles
R Duan, X Ma, Y Wang, J Bailey, AK Qin, Y Yang
CVPR2020, 2020
2662020
Jailbreak and guard aligned language models with only few in-context demonstrations
Z Wei, Y Wang, A Li, Y Mo, Y Wang
arXiv preprint arXiv:2310.06387, 2023
2052023
Unlearnable Examples: Making Personal Data Unexploitable
H Huang, X Ma, SM Erfani, J Bailey, Y Wang
ICLR 2021, 2021
2022021
Training High-Performance Low-Latency Spiking Neural Networks by Differentiation on Spike Representation
Q Meng, M Xiao, S Yan, Y Wang, Z Lin, ZQ Luo
CVPR 2022, 2022
1692022
Improving adversarial robustness via channel-wise activation suppressing
Y Bai, Y Zeng, Y Jiang, ST Xia, X Ma, Y Wang
ICLR 2021, 2021
1422021
Chaos is a Ladder: A New Theoretical Understanding of Contrastive Learning via Augmentation Overlap
Y Wang, Q Zhang, Y Wang, J Yang, Z Lin
ICLR 2022, 2022
1352022
Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks
H Huang, Y Wang, S Erfani, Q Gu, J Bailey, X Ma
NeurIPS 2021, 2021
1162021
Leveraged Weighted Loss for Partial Label Learning
H Wen, J Cui, H Hang, J Liu, Y Wang, Z Lin
ICML 2021, 2021
1162021
A novel consistent random forest framework: Bernoulli random forests
Y Wang, ST Xia, Q Tang, J Wu, X Zhu
IEEE transactions on neural networks and learning systems 29 (8), 3510-3523, 2017
115*2017
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Cikkek 1–20