Jun Fan
Jun Fan
Assistant Professor, Hong Kong Baptist University
Verifierad e-postadress på hkbu.edu.hk - Startsida
Citeras av
Citeras av
Regularization schemes for minimum error entropy principle
T Hu, J Fan, Q Wu, DX Zhou
Analysis and Applications 13 (04), 437-455, 2015
Learning theory approach to minimum error entropy criterion
T Hu, J Fan, Q Wu, DX Zhou
Journal of Machine Learning Research 14 (Feb), 377-397, 2013
Consistency analysis of an empirical minimum error entropy algorithm
J Fan, T Hu, Q Wu, DX Zhou
Applied and Computational Harmonic Analysis 41 (1), 164-189, 2016
A statistical learning approach to modal regression
Y Feng, J Fan, JAK Suykens
Journal of Machine Learning Research 21 (2), 1−35, 2020
Parameterized BLOSUM matrices for protein alignment
D Song, J Chen, G Chen, N Li, J Li, J Fan, D Bu, SC Li
IEEE/ACM transactions on computational biology and bioinformatics 12 (3 …, 2014
Learning rates for regularized least squares ranking algorithm
Y Zhao, J Fan, L Shi
Analysis and Applications 15 (06), 815-836, 2017
Structure-leveraged methods in breast cancer risk prediction
J Fan, Y Wu, M Yuan, D Page, J Liu, IM Ong, P Peissig, E Burnside
The Journal of Machine Learning Research 17 (1), 2956-2970, 2016
Comparing mammography abnormality features to genetic variants in the prediction of breast cancer in women recommended for breast biopsy
ES Burnside, J Liu, Y Wu, AA Onitilo, CA McCarty, CD Page, PL Peissig, ...
Academic radiology 23 (1), 62-69, 2016
Breast cancer risk prediction using electronic health records
Y Wu, ES Burnside, J Cox, J Fan, M Yuan, J Yin, P Peissig, A Cobian, ...
2017 IEEE International Conference on Healthcare Informatics (ICHI), 224-228, 2017
Sparsity and error analysis of empirical feature-based regularization schemes
X Guo, J Fan, DX Zhou
The Journal of Machine Learning Research 17 (1), 3058-3091, 2016
Utility of genetic testing in addition to mammography for determining risk of breast cancer depends on patient age
SI Feld, J Fan, M Yuan, Y Wu, KM Woo, R Alexandridis, ES Burnside
AMIA Summits on Translational Science Proceedings 2018, 81, 2018
Discriminatory power of common genetic variants in personalized breast cancer diagnosis
Y Wu, CK Abbey, J Liu, I Ong, P Peissig, AA Onitilo, J Fan, M Yuan, ...
Medical Imaging 2016: Image Perception, Observer Performance, and Technology …, 2016
Optimal learning with Gaussians and correntropy loss
F Lv, J Fan
Analysis and Applications, 1-18, 2019
Quantifying predictive capability of electronic health records for the most harmful breast cancer
Y Wu, J Fan, P Peissig, R Berg, AP Tafti, J Yin, M Yuan, D Page, J Cox, ...
Medical Imaging 2018: Image Perception, Observer Performance, and Technology …, 2018
Convergence analysis of distributed multi-penalty regularized pairwise learning
T Hu, J Fan, DH Xiang
Analysis and Applications 18 (01), 109-127, 2020
Comparison theorems on large-margin learning
J Fan, DH Xiang
arXiv preprint arXiv:1908.04470, 2019
An RKHS approach to estimate individualized treatment rules based on functional predictors.
J Fan, F Lv, L Shi
Math. Found. Comput. 2 (2), 169-181, 2019
Doubly robust estimation of average treatment effect revisited
K Guo, C Ye, J Fan, L Zhu
arXiv preprint arXiv:2005.14508, 2020
Quantitative convergence analysis of kernel based large-margin unified machines
J Fan, DH Xiang
Communications on Pure & Applied Analysis 19 (8), 4069, 2020
Comments on “Personalized dose finding using outcome weighted learning”
J Fan, M Yuan
Journal of the American Statistical Association 111 (516), 1524, 2017
Systemet kan inte utföra åtgärden just nu. Försök igen senare.
Artiklar 1–20