Welcome to Yuan Shi's Homepage
 

Research Interests

Machine Learning, Optimization, and Computer Vision


Experience

2010.8 -       Ph.D Program
Department of Computer Science, University of Southern California (USC), Los Angeles, USA

2009.8 - 2010.6   Visiting Scholar
Robotics Institute, Carnegie Mellon University (CMU), Pittsburgh, USA

2007.9 - 2007.12   Exchange Program
Department of Computer Science, City University of Hong Kong (CityU), HK

2005.9 - 2009.6   B. Eng Program
School of Software, Sun Yat-sen University (SYSU), Guangzhou, China


Publications

Yuan Shi, Aurelien Bellet and Fei Sha. Sparse Compositional Metric Learning. The Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI), 2014. (Oral)

Yuan Shi and Fei Sha. Information-Theoretical Learning of Discriminative Clusters for Unsupervised Domain Adaptation. International Conference on Machine Learning (ICML), 2012.

Boqing Gong, Yuan Shi, Fei Sha and Kristen Grauman. Geodesic Flow Kernel for Unsupervised Domain Adaptation. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2012. (Oral)

Yuan Shi, Yung-Kyun Noh, Fei Sha, and Daniel D. Lee. Learning Discriminative Metrics via Generative Models and Kernel Learning. NIPS Workshop "Beyond Mahalanobis: Supervised Large-Scale Learning of Similarity" , 2011. (Oral)

Huan Li, Yuan Shi, Mingyu Chen, Alexander Hauptmann and Zhang Xiong. Hybrid Active Learning for Cross-Domain Video Concept Detection. ACM Multimedia (ACM MM), 2010.

Yuan Shi, Minh Hoai Nguyen, Patrick Blitz, Brian French, Scott Fisk, Fernando De la Torre, Asim Smailagic et al. Personalized Stress Detection from Physiological Measurements. International symposium on quality of life technology, 2010.

Yuan Shi, Zhenzhong Lan, Wei Liu and Wei Bi. Extending Semi-Supervised Learning Methods for Inductive Transfer Learning. IEEE International Conference on Data Mining
(ICDM), 2009. (Oral)


Awards

2010  USC Annenberg Graduate Fellowship

2009  National Science Foundation (NSF) Travel Award for ICDM

2009  Meritorious Winner in Mathematical Contest in Modeling (MCM), USA