Liang Sun

I am a Ph.D. student in Department of Computer Science and Engineering, Arizona State University. My research interests include the following topics:

• Dimensionality reduction
• Sparse learning
• Data mining techniques for graph, and hypergraph
• Kernel learning
• Other interesting topics in data mining and machine learning

For more information of my research, please email me: sun.liang@asu.edu.    

Publications

1. Liang Sun, Shuiwang Ji, and Jieping Ye. A Least Squares Formulation for a Class of Generalized Eigenvalue Problems in Machine Learning. ICML 2009. PDF
2. 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. SIGKDD 2009. (Full presentation). PDF
3. Liang Sun, Shuiwang Ji, Shipeng Yu, and Jieping Ye. On the Equivalence Between Canonical Correlation Analysis and Orthonormalized Partial Least Squares. IJCAI 2009. PDF
4. Zheng Zhao, Liang Sun, Shipeng Yu, Huan Liu, and Jieping Ye. Multiclass Probabilistic Kernel Discriminant Analysis. IJCAI 2009. PDF
5. Liang Sun, Shuiwang Ji, and Jieping Ye. A least squares formulation for canonical correlation analysis. The Twenty-Fifth International Conference on Machine Learning (ICML 2008). PDF  Code
6. Liang Sun, Shuiwang Ji, and Jieping Ye. Hypergraph Spectral Learning for Multi-label Classification. The Fourteenth ACM SIGKDD International Conference On Knowledge Discovery and Data Mining (SIGKDD 2008). (Full presentation, 10% acceptance rate) PDF
7. Liang Sun, Shuiwang Ji, and Jieping Ye. Adaptive Diffusion Kernel Learning from Biological Networks for Protein Function Prediction. BMC Bioinformatics. 9:162, 2008. PDF
8. Shuiwang Ji, Liang Sun, Rong Jin, Sudhir Kumar, and Jieping Ye. Automated annotation of Drosophila gene expression patterns using a controlled vocabulary. Bioinformatics. 24(17):1881-1888, 2008. PDF
9. Shuiwang Ji, Liang Sun, Rong Jin, and Jieping Ye. Multi-label Multiple Kernel Learning. The Twenty-Second Annual Conference on Neural Information Processing Systems (NIPS 2008). PDF

Codes

• LS_CCA package: a least squares formulation for CCA. It also implements CCA, kernel CCA, least squares and kernel least squares.

Presentations

Some useful slides of my presentation.

• A survey of Several Nonlinear Optimization Algorithms
• A survey of hypergraph
• Diffusion kernel: an introduction
• Linear models for classification (Part1, Part2)
• EM algorithm