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ywangcy AT connect.ust.hk

Yaqing Wang (王雅晴)

Researcher, Baidu Research

I obtained my Ph.D degree in the Department of Computer Science and Engineering (CSE), Hong Kong University of Science and Technology (HKUST), 2019. During my Ph.D study period, I was co-supervised by Prof Lionel M. Ni and Prof. James T. Kwok. Before that, I obtained my Bachelor degree in School of Computer Science and Technology, Shandong University, 2014. Now I am working at Baidu Research.

Research Interests

My current research topics include:

  • Few-shot learning.
  • Sparse and low-rank learning.
  • Sample-dependent representation learning.
  • Natural language processing with knowledge graphs.
  • Biomedical applications.

Recent Publications

[ResearchGate]

A Scalable, Adaptive and Sound Nonconvex Regularizer for Low-rank Matrix Learning
Yaqing Wang, Quanming Yao, James T. Kwok, The Web Conference (WWW), 2021 [Link]

Generalized Convolutional Sparse Coding with Unknown Noise
Yaqing Wang, James T. Kwok, Lionel M. Ni, IEEE Transactions on Image Processing (TIP), 2020 [Link]

Generalizing from a Few Examples: A Survey on Few-Shot Learning
Yaqing Wang, Quanming Yao, James T. Kwok, Lionel M. Ni, ACM Computing Surveys (CSUR), 2020 [Link] [Git Repo for FSL Papers]

Online Convolutional Sparse Coding with Sample-Dependent Dictionary
Yaqing Wang, Quanming Yao, James T. Kwok, Lionel M. Ni, International Conference on Machine Learning (ICML), 2018 [Link] [PDF] [Code]

Scalable Online Convolutional Sparse Coding
Yaqing Wang, Quanming Yao, James T. Kwok, Lionel M. Ni, IEEE Transactions on Image Processing (TIP), 2018 [Link] [PDF] [Code]

Zero-Shot Learning with a Partial Set of Observed Attributes
Yaqing Wang, James T. Kwok, Quanming Yao, Lionel M. Ni, International Joint Conference on Neural Networks (IJCNN), 2017 [Link] [PDF]

Working Experience

  • Research Intern, 4Paradigm, January 2019 - September 2019

Selected Awards

Academic Service

  • Senior Program Committee Member: IJCAI 2021

  • Conference Reviewer / Program Committee Member: AAAI 2020-2021, ACML 2019-2021, AISTATS 2019-2021, ICML 2019, ICONIP 2019, NeurIPS 2019-2020, ICLR 2020-2021, IJCAI 2020-2021, IJCNN 2020-2021

  • Journal Reviewer: IEEE Transactions on Neural Networks and Learning Systems 2020-2021, Pattern Recognition 2020, Machine Learning Journal 2019-2020, Neural Networks 2020, ACML Journal Track 2019-2020, Applied Mathematical Modelling 2020, IEEE Computational Intelligence Magazine 2019, International Journal of Data Science and Analytics 2019-2020, Knowledge and Information Systems 2019-2020,

  • Session Chair: ICMLA 2020