Chuang Wang

Orcid: 0000-0002-8327-9363

Affiliations:
  • Chinese Academy of Sciences, National Laboratory of Pattern Recognition, NLPR, Institute of Automation, Beijing, China
  • University of Chinese Academy of Sciences, School of Artificial Intelligence, Beijing, China
  • Harvard University, Paulson School of Engineering and Applied Sciences, Cambridge, MA, USA (2015-2019)
  • Chinese Academy of Sciences, Institute of Theoretical Physics, Beijing, China (PhD 2015)


According to our database1, Chuang Wang authored at least 16 papers between 2014 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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Article 
PhD thesis 
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Links

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Bibliography

2024
Differentiable Proximal Graph Matching.
CoRR, 2024

Ensemble Quadratic Assignment Network for Graph Matching.
CoRR, 2024

2023
Deep representation learning for domain generalization with information bottleneck principle.
Pattern Recognit., November, 2023

Cycle-Consistent Weakly Supervised Visual Grounding With Individual and Contextual Representations.
IEEE Trans. Image Process., 2023

Towards prior gap and representation gap for long-tailed recognition.
Pattern Recognit., 2023

Class Incremental Learning with Self-Supervised Pre-Training and Prototype Learning.
CoRR, 2023

2022
Primitive Contrastive Learning for Handwritten Mathematical Expression Recognition.
Proceedings of the 26th International Conference on Pattern Recognition, 2022

2021
Prototype Augmentation and Self-Supervision for Incremental Learning.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Proxy Graph Matching with Proximal Matching Networks.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2019
A Solvable High-Dimensional Model of GAN.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018
Subspace Estimation From Incomplete Observations: A High-Dimensional Analysis.
IEEE J. Sel. Top. Signal Process., 2018

2017
Scaling Limit: Exact and Tractable Analysis of Online Learning Algorithms with Applications to Regularized Regression and PCA.
CoRR, 2017

The Scaling Limit of High-Dimensional Online Independent Component Analysis.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016
Online learning for sparse PCA in high dimensions: Exact dynamics and phase transitions.
Proceedings of the 2016 IEEE Information Theory Workshop, 2016

2015
Randomized Kaczmarz Algorithm for Inconsistent Linear Systems: An Exact MSE Analysis.
CoRR, 2015

2014
Randomized Kaczmarz algorithms: Exact MSE analysis and optimal sampling probabilities.
Proceedings of the 2014 IEEE Global Conference on Signal and Information Processing, 2014


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