Xin Tong

Assistant Professor of Data Sciences and Operations
Room / Office

PhD, Princeton University; BS, University of Toronto

Xin Tong's current research interests focus on asymmetric statistical learning, addressing challenges in the Neyman-Pearson classification paradigm, data distortion, sampling bias, asymmetric groups in classification and clustering, and partial knowledge in clustering and community detection. He has published papers in journals that include Science Advances, Journal of American Statistical Association, Journal of the Royal Statistical Society: Series B and the Journal of Machine Learning Research. Professor Tong's research has been partially supported by US NSF and NIH.
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Xin Tong () "Imbalanced classification: an objective-oriented review ,".
Wei Li, Xin Tong, Jingyi Li () "Bridging cost-sensitive and Neyman-Pearson paradigms for asymmetric binary classification ,".
Xiao Han, Xin Tong () "Individual-centered partial information in social networks ,".
Jingyi Li, Xin Tong () "Statistical hypothesis testing versus machine-learning binary classification: distinctions and guidelines ,"  Patterns (a Cell press journal).
Jessica Li, Xin Tong, Peter Bickel () "Generalized R2 Measures for a Mixture of Bivariate Linear Dependences ,".
Xiao Han, Xin Tong, Yingying Fan () "Eigen selection in spectral clustering: a theory guided practice. ,".
Xin Tong, Lucy Xia, Jiacheng Wang, Yang Feng () " Neyman-Pearson classification: parametrics and power enhancement ,"  Journal of Machine Learning Research (accepted).
Lucy Xia, Richard Zhao, Yanhui Wu, Xin Tong () "Intentional Control of Type I Error over Unconscious Data Distortion: a Neyman-Pearson Approach to Text Classification ,"  Journal of American Statistical Association .
Vivian Li, Shan Li, Xin Tong, Ling Deng, Hubin Shi, Jessica Li () "AIDE: annotation-assisted isoform discovery and abundance estimation from RNA-seq data ,"  Genome Research .
Xin Tong, Yang Feng, Jingyi Li () "Neyman-Pearson (NP) classification algorithms and NP receiver operating characteristics ,"  Science Advances .
Xin Tong, Jingyi Li () "Discussion of "Random-projection ensemble classification" by Cannings, T.I. and Samworth, R.J. ,"  79.
Jianqing Fan, Lei Qi, Xin Tong () "Penalized least squares estimation with weakly dependent data. ,"  Science China Mathematics,  59.
Jingyi Li, Xin Tong () "Genomic Applications of Neyman-Pearson Classification Paradigm ,"  Big Data Analytics in Genomics  Springer (New York)., 4.
Jianqing Fan, Yang Feng, Jiancheng Jiang, Xin Tong () "Feature Augmentation via Nonparametrics and Selection (FANS) in High Dimensional Classification ,"  Journal of the American Statistical Association   111, 149-158.