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ORCIDChuang Wang 0007
Person information
- affiliation: Chinese Academy of Sciences, National Laboratory of Pattern Recognition, NLPR, Institute of Automation, Beijing, China
- affiliation: University of Chinese Academy of Sciences, School of Artificial Intelligence, Beijing, China
- affiliation (2015-2019): Harvard University, Paulson School of Engineering and Applied Sciences, Cambridge, MA, USA
- affiliation (PhD 2015): Chinese Academy of Sciences, Institute of Theoretical Physics, Beijing, China
Other persons with the same name
- Chuang Wang — disambiguation page
- Chuang Wang 0001 — Huazhong University of Science and Technology, Wuhan, China
- Chuang Wang 0002 — Iowa State University, Ames, IO, USA
- Chuang Wang 0003
![[0000-0002-1981-5352]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0000-0002-1981-5352")
— South China University of Technology, School of Business Administration, Guangzhou, China (and 2 more) - Chuang Wang 0004 — Beijing University of Posts and Telecommunications, Beijing, China (and 1 more)
- Chuang Wang 0005 — Northeast Petroleum University, Sanya Offshore Oil & Gas Research Institute, China (and 1 more)
- Chuang Wang 0006 — Army Engineering University of PLA, College of Communications Engineering, Nanjing, China
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Journal Articles
- 2023
[j4]Ming-Liang Zhang, Xu-Yao Zhang, Chuang Wang, Cheng-Lin Liu:
Towards prior gap and representation gap for long-tailed recognition. Pattern Recognit. 133: 109012 (2023)- [j3]Jiao Zhang, Xu-Yao Zhang, Chuang Wang, Cheng-Lin Liu:
Deep representation learning for domain generalization with information bottleneck principle. Pattern Recognit. 143: 109737 (2023) - [j2]Ruisong Zhang, Chuang Wang, Cheng-Lin Liu:
Cycle-Consistent Weakly Supervised Visual Grounding With Individual and Contextual Representations. IEEE Trans. Image Process. 32: 5167-5180 (2023) - 2018
- [j1]Chuang Wang, Yonina C. Eldar, Yue M. Lu:
Subspace Estimation From Incomplete Observations: A High-Dimensional Analysis. IEEE J. Sel. Top. Signal Process. 12(6): 1240-1252 (2018)
Conference and Workshop Papers
- 2022
- [c7]Hong-Yu Guo, Chuang Wang, Fei Yin, Heng-Ye Liu, Jin-Wen Wu, Cheng-Lin Liu:
Primitive Contrastive Learning for Handwritten Mathematical Expression Recognition. ICPR 2022: 847-854 - 2021
- [c6]Haoru Tan, Chuang Wang, Sitong Wu, Tie-Qiang Wang, Xu-Yao Zhang, Cheng-Lin Liu:
Proxy Graph Matching with Proximal Matching Networks. AAAI 2021: 9808-9815 - [c5]Fei Zhu, Xu-Yao Zhang, Chuang Wang, Fei Yin, Cheng-Lin Liu:
Prototype Augmentation and Self-Supervision for Incremental Learning. CVPR 2021: 5871-5880 - 2019
- [c4]Chuang Wang, Hong Hu, Yue M. Lu:
A Solvable High-Dimensional Model of GAN. NeurIPS 2019: 13759-13768 - 2017
- [c3]Chuang Wang, Yue M. Lu:
The Scaling Limit of High-Dimensional Online Independent Component Analysis. NIPS 2017: 6638-6647 - 2016
- [c2]Chuang Wang, Yue M. Lu:
Online learning for sparse PCA in high dimensions: Exact dynamics and phase transitions. ITW 2016: 186-190 - 2014
- [c1]Ameya Agaskar, Chuang Wang, Yue M. Lu:
Randomized Kaczmarz algorithms: Exact MSE analysis and optimal sampling probabilities. GlobalSIP 2014: 389-393
Informal and Other Publications
- 2024
- [i9]Haoru Tan, Chuang Wang, Sitong Wu, Xu-Yao Zhang, Fei Yin, Cheng-Lin Liu:
Ensemble Quadratic Assignment Network for Graph Matching. CoRR abs/2403.06457 (2024) - [i8]Haoru Tan, Chuang Wang, Xu-Yao Zhang, Cheng-Lin Liu:
Differentiable Proximal Graph Matching. CoRR abs/2405.16479 (2024) - 2023
- [i7]Wenzhuo Liu, Xinjian Wu, Fei Zhu, Mingming Yu, Chuang Wang, Cheng-Lin Liu:
Class Incremental Learning with Self-Supervised Pre-Training and Prototype Learning. CoRR abs/2308.02346 (2023) - 2018
- [i6]Chuang Wang, Yonina C. Eldar, Yue M. Lu:
Subspace Estimation from Incomplete Observations: A High-Dimensional Analysis. CoRR abs/1805.06834 (2018) - [i5]Chuang Wang, Hong Hu, Yue M. Lu:
A Solvable High-Dimensional Model of GAN. CoRR abs/1805.08349 (2018) - 2017
- [i4]Chuang Wang, Yue M. Lu:
The Scaling Limit of High-Dimensional Online Independent Component Analysis. CoRR abs/1710.05384 (2017) - [i3]Chuang Wang, Jonathan Mattingly, Yue M. Lu:
Scaling Limit: Exact and Tractable Analysis of Online Learning Algorithms with Applications to Regularized Regression and PCA. CoRR abs/1712.04332 (2017) - 2016
- [i2]Chuang Wang, Yue M. Lu:
Online Learning for Sparse PCA in High Dimensions: Exact Dynamics and Phase Transitions. CoRR abs/1609.02191 (2016) - 2015
- [i1]Chuang Wang, Ameya Agaskar, Yue M. Lu:
Randomized Kaczmarz Algorithm for Inconsistent Linear Systems: An Exact MSE Analysis. CoRR abs/1502.00190 (2015)
Coauthor Index
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