Linglong Kong, PhD

Associate Professor, Faculty of Science - Mathematics & Statistical Sciences

Contact

Associate Professor, Faculty of Science - Mathematics & Statistical Sciences
Email
lkong@ualberta.ca

Overview

Research

Research Areas

Functional and Neuroimaging data analysis, Robust statistics and quantile regression, and Statistical machine learning.

Courses

STAT 541 - Statistics for Learning

The course focuses on statistical learning techniques, in particular those of supervised classification, both from statistical (logistic regression, discriminant analysis, nearest neighbours, and others) and machine learning background (tree-based methods, neural networks, support vector machines), with the emphasis on decision-theoretic underpinnings and other statistical aspects, flexible model building (regularization with penalties), and algorithmic solutions. Selected methods of unsupervised classification (clustering) and some related regression methods are covered as well. Prerequisite: Consent of the instructor.

Winter Term 2022

Browse more courses taught by Linglong Kong

Publications

Discussion of "Multivariate Quantiles and Multiple- Output Regression Quantiles: From L1 Optimization to Halfspace Depth"
Author(s): Kong, L. and Mizera, I.
Publication: Annals of Statistics
Volume: 38
Issue: 2
Page Numbers: 685-693

Multivariate Varying Coefficient Models for Functional Responses
Author(s): Zhu, H., Li, R., and Kong, L.
Publication: Annals of Statistics
Volume: 40
Issue: 5
Page Numbers: 2634-2666

Spatially Varying Coefficient Model for Neuroimaging Data with Jump Discontinuities
Author(s): Zhu, H., Fan, J., and Kong, L.
Publication: Journal of the American Statistical Association
Volume: 109
Issue: 507
Page Numbers: 1084-1098

Model-Robust Designs for Quantile Regression
Author(s): Kong, L. and Wiens, D.
Publication: Journal of the American Statistical Association
Volume: 110
Issue: 507
Page Numbers: 233-245

A General Framework for Quantile Estimation with Incomplete Data
Author(s): Han, P., Kong, L., Zhao, J., and Zhou, X.
Publication: Journal of Royal Statistical Society: Series B
Volume: 81
Issue: 2
Page Numbers: 305-333