Before coming to Stanford, I studied applied mathematics at Rice University. Outside of school, I am an avid cyclist with Stanford Cycling.
I will spend the 2015–2016 school year in the Department of Statistics at UC Berkeley as the Neyman Visiting Assistant Professor. In Autumn 2016, I will join the Department of Statistics at the University of Michigan as an Assistant Professor.
Huang Engineering Center
475 Via Ortega
Stanford, CA 94305
Communication-efficient sparse regression: a one-shot approach, Jason Lee*, Yuekai Sun*, Qiang Liu, Jonathan Taylor.
Archetype pursuit: A geometric approach to archetypal analysis and non-negative matrix factorization, Anil Damle, Yuekai Sun.
Exact post-selection inference with application to the lasso, Jason Lee, Dennis Sun, Yuekai Sun, Jonathan Taylor.
On the model selection consistency of regularized M-estimators, Jason Lee, Yuekai Sun, Jonathan Taylor, Electronic Journal of Statistics, to appear. A preliminary version appeared at NIPS 2013.
Learning mixtures of linear classifiers, Yuekai Sun, Stratis Ioannidis, Andrea Montanari, ICML 2014, Beijing, China.
Proximal Newton-type methods for minimizing composite functions, Jason Lee*, Yuekai Sun*, Michael Saunders, SIAM Journal on Optimization, 24(3), 1420–1443. A preliminary version appeared at NIPS 2012.
* co-first author
archetypes, a Python package for archetypal analysis and non-negative matrix factorization
The Selection Project, Python and R software for selective inference
PNOPT, a MATLAB package for minimizing composite functions
MS&E 318: Large-scale Numerical Optimization, Spring 2015