Jun Liu (jliu86@asu.edu or j.liu@asu.edu)

Depart of Computer Science and Engineering
Center for Evolutionary Functional Genomics
Arizona State University
Tempe, AZ 85281

Research Interest
  • Sparse Learning
  • Large-Scale Optimization
  • Kernel Methods
  • Dimensionality Reduction
Biography

I am currently a postdoc in the Machine Learning Research Lab, led by Dr. Jieping Ye.

I obtained my PhD from NUAA in November, 2007. My supervisor is Prof. Songcan Chen.

　

Software

I have developed the SLEP (Sparse Learning with Efficient Projections) Package, cooperated with Shuiwang Ji and Jieping Ye.

　

Academic Activities

Reviewers for Image Vision and Computing,  Information Science, Pattern Analysis & Applications, etc.

Volunteer for ICML 2009.

　

Publications (After Joining the Machine Learning Research Lab of ASU in 2008; my previous work can be found here.)

  • Jun Liu, Jianhui Chen, and Jieping Ye. Large-Scale Sparse Logistic Regression. The Fifteenth ACM SIGKDD International Conference On Knowledge Discovery and Data Mining (SIGKDD 2009). Full Presentation. PDF  Code

  • Jun Liu and Jieping Ye. Efficient Euclidean Projections in Linear Time. The Twenty-Sixth International Conference on Machine Learning (ICML 2009). PDF Code

  • Jun Liu, Shuiwang Ji, and Jieping Ye. Accelerated Multi-task Feature Learning. The Twenty-Fifth Conference on Uncertainty in Artificial Intelligence (UAI 2009). PDF Code

  • Jun Liu, Jianhui Chen, Songcan Chen, and Jieping Ye. Learning the Optimal Neighborhood Kernel for Classification. The Twenty-first International Joint Conference on Artificial Intelligence (IJCAI 2009). PDF

  • Liang Sun, Jun Liu, Jianhui Chen, and Jieping Ye. Efficient Recovery of Jointly Sparse Vectors. The Twenty-Third Annual Conference on Neural Information Processing Systems (NIPS 2009).

  • Shui Huang, Jing Li, Liang Sun, Jun Liu, Teresa Wu, Kewei Chen, Adam Fleisher, Eric Reiman, and Jieping Ye. Learning Brain Connectivity of Alzheimer's Disease from Neuroimaging Data. The Twenty-Third Annual Conference on Neural Information Processing Systems (NIPS 2009).

  • Liang Sun, Rinkal Patel, Jun Liu, Kewei Chen, Teresa Wu, Jing Li, Eric Reiman, and Jieping Ye. Mining Brain Region Connectivity for Alzheimer's Disease Study via Sparse Inverse Covariance Estimation. The Fifteenth ACM SIGKDD International Conference On Knowledge Discovery and Data Mining (SIGKDD 2009). Full Presentation.

  • Jianhui Chen, Lei Tang, Jun Liu, and Jieping Ye. A Convex Formulation for Learning Shared Structures from Multiple Tasks. The Twenty-Sixth International Conference on Machine Learning (ICML 2009).