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Pengfei Chen 0003
Person information
- affiliation: Tencent Technology, Shenzhen, China
- affiliation: Chinese University of Hong Kong, Department of Computer Science and Engineering, Hong Kong
Other persons with the same name
- Pengfei Chen — disambiguation page
- Pengfei Chen 0001 — Lanzhou University, School of Information Science and Engineering, China
- Pengfei Chen 0002 — Sun Yat-sen University, School of Data Science and Computer, Guangzhou, China (and 1 more)
- Pengfei Chen 0004 — University of Chinese Academy of Sciences, Beijing, China
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2020 – today
- 2022
- [c6]Donghao Zhou, Pengfei Chen, Qiong Wang, Guangyong Chen, Pheng-Ann Heng:
Acknowledging the Unknown for Multi-label Learning with Single Positive Labels. ECCV (24) 2022: 423-440 - [i10]Donghao Zhou, Pengfei Chen, Qiong Wang, Guangyong Chen, Pheng-Ann Heng:
Acknowledging the Unknown for Multi-label Learning with Single Positive Labels. CoRR abs/2203.16219 (2022) - 2021
- [c5]Hongyao Tang, Zhaopeng Meng, Guangyong Chen, Pengfei Chen, Chen Chen, Yaodong Yang, Luo Zhang, Wulong Liu, Jianye Hao:
Foresee then Evaluate: Decomposing Value Estimation with Latent Future Prediction. AAAI 2021: 9834-9842 - [c4]Pengfei Chen, Junjie Ye, Guangyong Chen, Jingwei Zhao, Pheng-Ann Heng:
Beyond Class-Conditional Assumption: A Primary Attempt to Combat Instance-Dependent Label Noise. AAAI 2021: 11442-11450 - [c3]Pengfei Chen, Junjie Ye, Guangyong Chen, Jingwei Zhao, Pheng-Ann Heng:
Robustness of Accuracy Metric and its Inspirations in Learning with Noisy Labels. AAAI 2021: 11451-11461 - [c2]Pengfei Chen, Guangyong Chen, Junjie Ye, Jingwei Zhao, Pheng-Ann Heng:
Noise against noise: stochastic label noise helps combat inherent label noise. ICLR 2021 - [i9]Hongyao Tang, Jianye Hao, Guangyong Chen, Pengfei Chen, Chen Chen, Yaodong Yang, Luo Zhang, Wulong Liu, Zhaopeng Meng:
Foresee then Evaluate: Decomposing Value Estimation with Latent Future Prediction. CoRR abs/2103.02225 (2021) - 2020
- [i8]Pengfei Chen, Junjie Ye, Guangyong Chen, Jingwei Zhao, Pheng-Ann Heng:
Robustness of Accuracy Metric and its Inspirations in Learning with Noisy Labels. CoRR abs/2012.04193 (2020) - [i7]Pengfei Chen, Junjie Ye, Guangyong Chen, Jingwei Zhao, Pheng-Ann Heng:
Beyond Class-Conditional Assumption: A Primary Attempt to Combat Instance-Dependent Label Noise. CoRR abs/2012.05458 (2020)
2010 – 2019
- 2019
- [c1]Pengfei Chen, Benben Liao, Guangyong Chen, Shengyu Zhang:
Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels. ICML 2019: 1062-1070 - [i6]Pengfei Chen, Benben Liao, Guangyong Chen, Shengyu Zhang:
Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels. CoRR abs/1905.05040 (2019) - [i5]Guangyong Chen, Pengfei Chen, Yujun Shi, Chang-Yu Hsieh, Benben Liao, Shengyu Zhang:
Rethinking the Usage of Batch Normalization and Dropout in the Training of Deep Neural Networks. CoRR abs/1905.05928 (2019) - [i4]Hongyao Tang, Jianye Hao, Guangyong Chen, Pengfei Chen, Zhaopeng Meng, Yaodong Yang, Li Wang:
Disentangling Dynamics and Returns: Value Function Decomposition with Future Prediction. CoRR abs/1905.11100 (2019) - [i3]Pengfei Chen, Weiwen Liu, Chang-Yu Hsieh, Guangyong Chen, Shengyu Zhang:
Utilizing Edge Features in Graph Neural Networks via Variational Information Maximization. CoRR abs/1906.05488 (2019) - [i2]Pengfei Chen, Benben Liao, Guangyong Chen, Shengyu Zhang:
A Meta Approach to Defend Noisy Labels by the Manifold Regularizer PSDR. CoRR abs/1906.05509 (2019) - [i1]Guangyong Chen, Pengfei Chen, Chang-Yu Hsieh, Chee-Kong Lee, Benben Liao, Renjie Liao, Weiwen Liu, Jiezhong Qiu, Qiming Sun, Jie Tang, Richard S. Zemel, Shengyu Zhang:
Alchemy: A Quantum Chemistry Dataset for Benchmarking AI Models. CoRR abs/1906.09427 (2019)
Coauthor Index
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