Yisen Wang

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Xingjun MaSchool of Computer Science, Fudan UniversityAdresse e-mail validée de unimelb.edu.au
Yifei WangPostdoc, MIT CSAILAdresse e-mail validée de mit.edu
James BaileyProfessor, School of Computing and Information Systems, University of MelbourneAdresse e-mail validée de unimelb.edu.au
Zhouchen LinProfessor, Peking University; Fellow of IEEE, IAPR, CSIG & AAIA; ex-VP of Samsung ResearchAdresse e-mail validée de pku.edu.cn
Dongxian WuBytedanceAdresse e-mail validée de bytedance.com
Quanquan GuAssociate Professor of Computer Science, UCLAAdresse e-mail validée de cs.ucla.edu
Bo LiUniversity of Illinois at Urbana–ChampaignAdresse e-mail validée de illinois.edu
Mingjie LiPostdoc Researcher, CISPAAdresse e-mail validée de pku.edu.cn
Le SongGenBio AI, Mohamed bin Zayed University of Artificial IntelligenceAdresse e-mail validée de mbzuai.ac.ae
Weiyang LiuMax Planck Institute for Intelligent SystemsAdresse e-mail validée de tuebingen.mpg.de
Hongyuan ZhaThe Chinese University of Hong Kong, ShenzhenAdresse e-mail validée de cuhk.edu.cn
Dawn SongProfessor of Computer Science, UC BerkeleyAdresse e-mail validée de cs.berkeley.edu
Xingquan (Hill) ZhuIEEE Fellow, Dept. of Electrical Eng. and Comp. Science, Florida Atlantic UniversityAdresse e-mail validée de fau.edu
Qionghai DaiTsinghua UniversityAdresse e-mail validée de tsinghua.edu.cn
Zhi-Hua ZhouNanjing UniversityAdresse e-mail validée de nju.edu.cn

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Yisen Wang

Assistant Professor, Peking University

Adresse e-mail validée de pku.edu.cn - Page d'accueil

Machine Learning Self-Supervised Learning Large Language Models Safety


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Symmetric cross entropy for robust learning with noisy labels Y Wang, X Ma, Z Chen, Y Luo, J Yi, J Bailey ICCV 2019, 2019	1131	2019
Improving Adversarial Robustness Requires Revisiting Misclassified Examples Y Wang, D Zou, J Yi, J Bailey, X Ma, Q Gu ICLR2020, 2020	863	2020
Characterizing adversarial subspaces using local intrinsic dimensionality X Ma, B Li, Y Wang, SM Erfani, S Wijewickrema, ME Houle, ... ICLR2018, 2018	863	2018
Adversarial Weight Perturbation Helps Robust Generalization D Wu, S Xia, Y Wang NeurIPS 2020, 2020	812	2020
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	548	2019
Normalized Loss Functions for Deep Learning with Noisy Labels X Ma, H Huang, Y Wang, S Romano, S Erfani, J Bailey ICML2020, 2020	517	2020
Dimensionality-Driven Learning with Noisy Labels X Ma, Y Wang, ME Houle, S Zhou, SM Erfani, ST Xia, S Wijewickrema, ... ICML2018, 2018	480	2018
On the Convergence and Robustness of Adversarial Training Y Wang, X Ma, J Bailey, J Yi, B Zhou, Q Gu ICML2019, 2019	436	2019
Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets D Wu, Y Wang, ST Xia, J Bailey, X Ma ICLR2020, 2020	401	2020
Iterative Learning with Open-set Noisy Labels Y Wang, W Liu, X Ma, J Bailey, H Zha, L Song, ST Xia CVPR2018, 2018	379	2018
Adversarial Neuron Pruning Purifies Backdoored Deep Models D Wu, Y Wang NeurIPS 2021, 2021	312	2021
Adversarial Camouflage: Hiding Physical-World Attacks with Natural Styles R Duan, X Ma, Y Wang, J Bailey, AK Qin, Y Yang CVPR2020, 2020	267	2020
Unlearnable Examples: Making Personal Data Unexploitable H Huang, X Ma, SM Erfani, J Bailey, Y Wang ICLR 2021, 2021	199	2021
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	181	2023
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	164	2022
Improving adversarial robustness via channel-wise activation suppressing Y Bai, Y Zeng, Y Jiang, ST Xia, X Ma, Y Wang ICLR 2021, 2021	144	2021
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	140	2022
Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks H Huang, Y Wang, S Erfani, Q Gu, J Bailey, X Ma NeurIPS 2021, 2021	117	2021
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
Leveraged Weighted Loss for Partial Label Learning H Wen, J Cui, H Hang, J Liu, Y Wang, Z Lin ICML 2021, 2021	114	2021

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