Yu Zhang

 

 

Research Associate

Department of Computer Science and Engineering
Hong Kong University of Science and Technology

Email:   zhangyu at cse dot ust dot hk

 

Research Interests

My current research interests include artificial intelligence, machine learning, pattern recognition, and data mining. I am especially interested in multi-task learning, transfer learning, semi-supervised learning, dimensionality reduction, metric learning, and their applications.

 

Selected Publications

Journal Papers
  • Qing Bao, William K. Cheung, Yu Zhang, and Jiming Liu. A Component-based Diffusion Model with Structural Diversity for Social Networks. 
    Accepted by IEEE Transactions on Cybernetics (TCYB).
  • Yu Zhang, William K. Cheung, and Jiming Liu. A Unified Framework for Epidemic Prediction based on Poisson Regression. IEEE Transactions on 
    Knowledge and Data Engineering (TKDE),  27(11): 2878-2892, 2015. (Link)
  • Deming Zhai, Yu Zhang, Dit-Yan Yeung, Hong Chang, Xilin Chen, and Wen Gao. Instance-Specific Canonical Correlation Analysis. Neurocomputing,
    155(1): 205-218, 2015. (Link)
Conference Papers
  • Lei Han, Yu Zhang, and Tong Zhang. Fast Component Pursuit for Large-Scale Inverse Covariance Estimation. In: Proceedings of the Twenty-Second 
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), San Francisco, California, USA, 2016. (The first two authors 
    contributed equally)
  • Lei Han, Yu Zhang, Xiu-Feng Wan, and Tong Zhang. Generalized Hierarchical Sparse Model for Arbitrary-Order Interactive Antigenic Sites Identification
    in Flu Virus Data. In: Proceedings of the Twenty-Second ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), San Francisco, 
    California, USA, 2016.
  • Shuangyin Li, Rong Pan, Yu Zhang, and Qiang Yang. Correlated Tag Learning in Topic Model. In: Proceedings of the 32nd Conference on 
    Uncertainty in Artificial Intelligence (UAI), New York City, NY, USA, 2016.
  • Lei Han and Yu Zhang. Multi-Stage Multi-Task Learning with Reduced Rank. In: Proceedings of the 30th AAAI Conference on Artificial 
    Intelligence (AAAI), Phoenix, Arizona, USA, 2016. (Both authors contributed equally)
  • Lei Han and Yu Zhang. Reduction Techniques for Graph-based Convex Clustering. In: Proceedings of the 30th AAAI Conference on Artificial 
    Intelligence (AAAI), Phoenix, Arizona, USA, 2016. (Both authors contributed equally)
  • Yu Zhang. Parallel Multi-Task Learning. In: Proceedings of the IEEE International Conference on Data Mining (ICDM), Atlantic City, New Jersey, 
    USA, 2015.
  • Lei Han and Yu Zhang. Learning Tree Structure in Multi-Task Learning. In: Proceedings of the 21st ACM SIGKDD Conference on Knowledge 
    Discovery and Data Mining (KDD), Sydney, 2015. (Both authors contributed equally) (Link)
  • Rui Chen, Qian Xiao, Yu Zhang, and Jianliang Xu. Differentially Private High-Dimensional Data Publishing via Sampling-Based Inference. In: 
    Proceedings of the 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), Sydney, 2015. (Link)
Ph.D. Thesis
  • Yu Zhang. A Probabilistic Framework for Learning Task Relationships in Multi-Task Learning. Department of Computer Science and Engineering, 
The Hong Kong University of Science and Technology, August, 2011. (pdf)
Book Chapters

 

Honors and Awards

  • Best Student Paper Award, WI Conference, 2013

  • SENG PhD Research Excellence Award, HKUST, 2011

  • Best Paper Award, UAI Conference, 2010

  • Overseas Research Award, HKUST, 2010-2011

  • Research Travel Award, NIPS&UAI&AISTATS, 2010

  • Champion, Postgraduate Student Research Paper Competition 2010, IEEE (Hong Kong) Computational Intelligence Chapter

  • Research Travel Award, HKUST, 2009

  • Second Runner-Up Award, Postgraduate Student Research Paper Competition 2009, IEEE (Hong Kong) Computational Intelligence Chapter

  • Postgraduate Scholarship, HKUST (2007, 2008, 2009, 2010, 2011)

  • Best Paper Award, Jiangsu Province Computer Society, 2005

  • Excellent Undergraduate Scholarship, Nanjing University (2001, 2002, 2003, 2004)

 

Professional Activities

Journal Reviewer

Journal of Machine Learning Research

IEEE Transactions on Pattern Analysis and Machine Intelligence

IEEE Transactions on Knowledge and Data Engineering

IEEE Transactions on Multimedia

IEEE Transactions on Neural Network and Learning Systems

IEEE Transactions on Systems, Man, and Cybernetics, Part B

ACM Transactions on Intelligent Systems and Technology

Neural Computation

Statistical Analysis and Data Mining

Pattern Recognition

Knowledge and Information Systems

Pattern Recognition Letter

Information Sciences

Neurocomputing

Applied Intelligence

ACTA AUTOMATICA SINICA

Frontiers of Computer Science in China

Journal of Software

 

PC Member

NIPS 2016, ICML 2016, KDD 2016, IJCAI 2016, AAAI 2016, UAI 2016, PRICAI 2016

NIPS 2015, KDD 2015, IJCAI 2015, UAI 2015, ICDM 2015

NIPS 2014, ICML 2014, UAI 2014, ICPR 2014, PRICAI 2014

NIPS 2013, IJCAI 2013, SDM 2013, ACML 2013

UAI 2012

 

 

Teaching Experience

 

  • HKBU COMP7930: Big Data Analytics (Spring 2015)

  • HKBU COMP7390: Algorithms for Financial Information Systems (Fall 2014)

  • HKBU COMP3790: Advanced Algorithm Design, Analysis and Implementation (Fall 2014)

  • HKBU COMP7070: Advanced Topics in Machine Learning (Fall 2013)

  • HKBU COMP7340: Enterprise Application Architecture and Integration (Spring 2013)

  • HKBU Short Course: Classic Data Mining Algorithms (Winter 2012)

 

Links