Department of Data Sciences and Operations
Marshall School of Business
University of Southern California
Los Angeles, CA 90089
Office: HOH 504
Mailing address: BRI 401
Email: xint AT marshall.usc.edu
- 2012 Ph.D. in Operations Research Princeton University
- 2007 B.S. in Mathematics The University of Toronto
- Statistical learning theory
- High-dimensional classification
- Social and economic networks
* corresponding author
- Tong, X.*, Feng, Y. and Zhao, A. (2016), A survey on Neyman-Pearson classification and suggestions for future research, Wiley Interdisciplinary Reviews: Computational Statistics, 8, 64-81.
- Fan, J., Feng, Y., Jiang, J., and Tong, X. (2015), Feature augmentation via nonparametrics and selection (FANS) in high dimensional classification, Journal of the American Statistical Association, accepted.
- Fan, J., Tong, X.*, and Zeng, Y. (2015), Multi-agent inference in social networks: a finite population learning approach, Journal of the American Statistical Association, 110, 149-158.
- Tong, X.* (2013), A plug-in approach to Neyman-Pearson classification, Journal of Machine Learning Research, 14, 3011-3040.
- Fan, J., Feng, Y., and Tong, X.* (2012), A road to classification in high dimensional space: the regularized optimal affine discriminant, Journal of the Royal Statistical Society: Series B, 74, 745-771.
- Rigollet, P. and Tong, X. (2011) Neyman-Pearson classification under a strict constraint, the Conference on Learning Theory (COLT).
- Rigollet, P. and Tong, X. (2011) Neyman-Pearson classification, convexity and stochastic constraints, Journal of Machine Learning Research, 12, 2825-2849.
- 2014 Zumberge Individual Fund, University of Southern California
- 2013 The Zellner Thesis Award in Business and Economic Statistics, American Statistical Association
- 2011 Laha Travel Award, Institute of Mathematical Statistics