| MULTIVARIATE QUANTILES AND MULTIPLE-OUTPUT REGRESSION QUANTILES: FROM L ₁ OPTIMIZATION TO HALFSPACE DEPTH [with Discussion and Rejoinder] M Hallin, D Paindaveine, M Šiman, Y Wei, R Serfling, Y Zuo, L Kong, ... The Annals of Statistics, 635-703, 2010 | 171 | 2010 |
| Quantile tomography: Using quantiles with multivariate data L Kong, I Mizera Statistica Sinica 22, 1589-1610, 2012 | 123 | 2012 |
| Multivariate varying coefficient model for functional responses H Zhu, R Li, L Kong Annals of statistics 40 (5), 2634, 2012 | 85 | 2012 |
| FADTTS: functional analysis of diffusion tensor tract statistics H Zhu, L Kong, R Li, M Styner, G Gerig, W Lin, JH Gilmore NeuroImage 56 (3), 1412-1425, 2011 | 73 | 2011 |
| Spatially varying coefficient model for neuroimaging data with jump discontinuities H Zhu, J Fan, L Kong Journal of the American Statistical Association 109 (507), 1084-1098, 2014 | 70 | 2014 |
| Smooth depth contours characterize the underlying distribution L Kong, Y Zuo Journal of Multivariate Analysis 101 (9), 2222-2226, 2010 | 43 | 2010 |
| Utilization of health research in acute care settings in Alberta CA Estabrooks, JE Squires, AM Adachi, L Kong, PG Norton Tech. Rep., Faculty of Nursing, University of Alberta, Edmonton, Canada, 2008 | 37* | 2008 |
| Exposure to urban air pollution and bone health in clinically healthy six-year-old children L Calderón-Garcidueñas, A Mora-Tiscareño, M Franco-Lira, ... Arhiv za higijenu rada i toksikologiju 64 (1), 23-23, 2013 | 28 | 2013 |
| Partial functional linear quantile regression for neuroimaging data analysis D Yu, L Kong, I Mizera Neurocomputing 195, 74-87, 2016 | 21 | 2016 |
| Growing story forest online from massive breaking news B Liu, D Niu, K Lai, L Kong, Y Xu Proceedings of the 2017 ACM on Conference on Information and Knowledge …, 2017 | 17* | 2017 |
| A review of statistical methods in imaging genetics FS Nathoo, L Kong, H Zhu, Alzheimer's Disease Neuroimaging Initiative Canadian Journal of Statistics 47 (1), 108-131, 2019 | 16 | 2019 |
| Examining the role of context in Alzheimer care centers: A pilot study technical report J Squires, C Estabrooks, L Kong, S Brooker Edmonton, Alberta: Faculty of Nursing, University of Alberta, 2009 | 13 | 2009 |
| Distributional reinforcement learning for efficient exploration B Mavrin, S Zhang, H Yao, L Kong, K Wu, Y Yu Proceedings of the Thirty-sixth International Conference on Machine Learning, 2019 | 12* | 2019 |
| Regularized quantile regression under heterogeneous sparsity with application to quantitative genetic traits Q He, L Kong, Y Wang, S Wang, TA Chan, E Holland Computational statistics & data analysis 95, 222-239, 2016 | 12 | 2016 |
| Clinically relevant reperfusion in acute ischemic stroke: MTT performs better than Tmax and TTP AL Ford, H An, L Kong, H Zhu, KD Vo, WJ Powers, W Lin, JM Lee Translational stroke research 5 (3), 415-421, 2014 | 11 | 2014 |
| Context and Research Use in the Care of Children: A Pilot Study AM Hutchinson, AM Adachi, L Kong, CA Estabrooks, B Stevens | 11 | 2008 |
| QUOTA: The quantile option architecture for reinforcement learning S Zhang, H Yao Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 5797-5804, 2019 | 9 | 2019 |
| HIV-associated sensory polyneuropathy and neuronal injury are associated with miRNA–455-3p induction EL Asahchop, WG Branton, A Krishnan, PA Chen, D Yang, L Kong, ... JCI insight 3 (23), 2018 | 9 | 2018 |
| Local region sparse learning for image-on-scalar regression Y Chen, X Wang, L Kong, H Zhu arXiv preprint arXiv:1605.08501, 2016 | 9 | 2016 |
| House price modeling over heterogeneous regions with hierarchical spatial functional analysis B Liu, B Mavrin, D Niu, L Kong 2016 IEEE 16th International Conference on Data Mining (ICDM), 1047-1052, 2016 | 8 | 2016 |
Hongtu ZhuProfessor of Biostatistics, The University of North Carolina at Chapel HillVerified email at email.unc.edu
