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王奕森

作者:   时间:2020-09-14   点击数:



王奕森

职称:研究员/助理教授,博士生导师

研究所:信息科学中心

研究领域:机器学习

电话:86-10-62755097

电子邮件:yisen.wang@pku.edu.cn

个人主页:https://yisenwang.github.io/

教育背景

2018年博士毕业于清华大学计算机系

主要研究领域

机器学习深度学习,对抗学习,图学习,弱监督学习

代表性学术论著

1.Dongxian Wu, Shu-Tao Xia,Yisen Wang#; “Adversarial Weight Perturbation Helps Robust Generalization”, Neural Information Processing Systems (NeurIPS 2020)

2.Yisen Wang*, Xingjun Ma*, James Bailey, Jinfeng Yi, Bowen Zhou, Quanquan Gu; “On the Convergence and Robustness of Adversarial Training”, International Conference on Machine Learning (ICML 2019)

3.Yisen Wang*, Difan Zou*, Jinfeng Yi, James Bailey, Xingjun Ma, Quanquan Gu; “Improving Adversarial Robustness Requires Revisiting Misclassified Examples”, International Conference on Learning Representations (ICLR 2020)

4.Dongxian Wu,Yisen Wang#, Shu-Tao Xia, James Bailey, Xingjun Ma; “Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets”, International Conference on Learning Representations (ICLR 2020)

5.Xingjun Ma*, Hanxun Huang*,Yisen Wang#, Simone Romano, Sarah Erfani, James Bailey; “Normalized Loss Functions for Deep Learning with Noisy Labels”, International Conference on Machine Learning (ICML 2020)

6.Yisen Wang*, Xingjun Ma*, Zaiyi Chen, Yuan Luo, Jinfeng Yi, James Bailey; “Symmetric Cross Entropy for Robust Learning with Noisy Labels”, International Conference on Computer Vision (ICCV 2019)

7.Yisen Wang, Weiyang Liu, Xingjun Ma, James Bailey, Hongyuan Zha, Le Song, Shu-Tao Xia; “Iterative Learning with Open-set Noisy Labels”, IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2018)


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