Eng · 繁體 · 简体

 [   ] 

Prof. WANG Junhui (王軍輝)

PhD – University of Minnesota, USA
BS – Peking University, China

Professor

Contact Information

Office: LAU-16-229 
Phone: (+852) 3442-2153
Fax: (+852) 3442-0515
Email: j.h.wang@cityu.edu.hk
Web: Personal Homepage

Research Interests

  • Statistical machine learning
Prof. Junhui Wang received his BSc from Peking University and PhD from University of Minnesota. Before joining CityU, he was Associate professor at University of Illinois at Chicago. His main research interest is on statistical machine learning and its broad applications in biomedicine, engineering, finance, IT and other data-related areas.


Publications Show All Publications Show Prominent Publications


Journal

  • Zhen, Y. & Wang, J. (2021). Community detection in general hypergraph via graph embedding. Journal of American Statistical Association. In press.
  • Zhang, J. , He, X. & Wang, J. (2021). Directed community detection with network embedding. Journal of American Statistical Association. In press.
  • Dai, B. , Shen, X. & Wang, J. (2021). Embedding learning. Journal of American Statistical Association. In press.
  • Dai, B. , Shen, X. , Wang, J. & Qu, A. (2021). Scalable collaborative ranking for personalized prediction. Journal of the American Statistical Association. 116. 1215 - 1223.
  • Dai, B. , Wang, J. , Shen, X. & Qu, A. (2019). Smooth neighborhood recommender systems. Journal of Machine Learning Research. 20(16). 1 - 24.
  • Bi, X. , Qu, A. , Wang, J. & Shen, X. (2017). A group-specific collaborative recommender. Journal of the American Statistical Association. 112. 1344 - 1353.
  • Wang, J. , Shen, X. , Sun, Y. & Qu, A. (2017). Automatic summarization by existing and novel tags. Biometrika. 104. 273 - 290.
  • Wang, J. , Shen, X. , Sun, Y. & Qu, A. (2016). Classification with unstructured predictors and an application to sentiment analysis. Journal of the American Statistical Association. 111. 1242 - 1253.
  • Yang, L. , Lv, S. & Wang, J. (2016). Model-free variable selection in reproducing kernel Hilbert space. Journal of Machine Learning Research. 17(78). 1 - 24.
  • Sun, W. , Wang, J. & Fang, Y. (2013). Consistent selection of tuning parameters in high-dimensional penalized regression. Journal of Machine Learning Research. 14. 3419 - 3440.
  • Wang, J. (2010). Consistent selection of the number of clusters via cross validation. Biometrika. 97. 893 - 904.
  • Wang, J. , Shen, X. & Pan, W. (2009). On large margin hierarchical classification with multiple paths. Journal of the American Statistical Association. 104. 1213 - 1223.
  • Wang, J. , Shen, X. & Pan, W. (2008). On efficient large margin semisupervised learning: methodology and theory. Journal of Machine Learning Research. 10. 719 - 742.
  • Wang, J. , Shen, X. & Liu, Y. (2008). Probability estimation for large margin classifiers. Biometrika. 95. 149 - 167.
  • Wang, J. & Shen, X. (2007). Large margin semi-supervised learning. Journal of Machine Learning Research. 8. 1867 - 1891.

Conference Paper

  • Lv, S. , Wang, J. , Liu, J. & Liu, Y. (2021). Improved learning rates of a functional Lasso-type SVM with sparse multi-kernel representation. NeurIPS, spotlight.


Last update date : 31 Oct 2021