Hanyuan Hang
Hanyuan Hang
Assistant Professor, University of Twente
Verified email at - Homepage
Cited by
Self-Supervised Random Forest on Transformed Distribution for Anomaly Detection
J Liu, H Wang, H Hang, S Ma, X Shen, Y Shi
IEEE Transactions on Neural Networks and Learning Systems, 2024
Transfer Learning under Covariate Shift: Local -Nearest Neighbours Regression with Heavy-Tailed Design
P Zamolodtchikov, H Hang
arXiv preprint arXiv:2401.11554, 2024
Class Probability Matching Using Kernel Methods for Label Shift Adaptation
H Wen, A Betken, H Hang
arXiv preprint arXiv:2312.07282, 2023
Bagged Regularized -Distances for Anomaly Detection
Y Cai, Y Ma, H Yang, H Hang
arXiv preprint arXiv:2312.01046, 2023
Bagged -Distance for Mode-Based Clustering Using the Probability of Localized Level Sets
H Hang
arXiv preprint arXiv:2210.09786, 2022
Random forest density estimation
H Wen, H Hang
International Conference on Machine Learning, 23701-23722, 2022
Llp-gan: a gan-based algorithm for learning from label proportions
J Liu, B Wang, H Hang, H Wang, Z Qi, Y Tian, Y Shi
IEEE transactions on neural networks and learning systems 34 (11), 8377-8388, 2022
Under-bagging nearest neighbors for imbalanced classification
H Hang, Y Cai, H Yang, Z Lin
Journal of Machine Learning Research 23 (118), 1-63, 2022
Local Adaptivity of Gradient Boosting in Histogram Transform Ensemble Learning
H Hang
arXiv preprint arXiv:2112.02589, 2021
Optimal learning with anisotropic Gaussian SVMs
H Hang, I Steinwart
Applied and Computational Harmonic Analysis 55, 337-367, 2021
GAN-CL: Generative adversarial networks for learning from complementary labels
J Liu, H Hang, B Wang, B Li, H Wang, Y Tian, Y Shi
IEEE transactions on cybernetics 53 (1), 236-247, 2021
GBHT: Gradient boosting histogram transform for density estimation
J Cui, H Hang, Y Wang, Z Lin
International Conference on Machine Learning, 2233-2243, 2021
Leveraged weighted loss for partial label learning
H Wen, J Cui, H Hang, J Liu, Y Wang, Z Lin
International conference on machine learning, 11091-11100, 2021
Histogram transform ensembles for large-scale regression
H Hang, Z Lin, X Liu, H Wen
Journal of Machine Learning Research 22 (95), 1-87, 2021
Boosted histogram transform for regression
Y Cai, H Hang, H Yang, Z Lin
International Conference on Machine Learning, 1251-1261, 2020
Matrix infinitely divisible series: Tail inequalities and their applications
C Zhang, X Gao, MH Hsieh, H Hang, D Tao
IEEE Transactions on Information Theory 66 (2), 1099-1117, 2019
Density-based Clustering with Best-scored Random Forest
H Hang, Y Cai, H Yang
arXiv preprint arXiv:1906.10094, 2019
Kernel density estimation for dynamical systems
H Hang, I Steinwart, Y Feng, JAK Suykens
Journal of Machine Learning Research 19 (35), 1-49, 2018
Matrix Infinitely Divisible Series: Tail Inequalities and Applications in Optimization.
C Zhang, X Gao, MH Hsieh, H Hang, D Tao
arXiv preprint arXiv:1809.00781, 2018
A Bernstein-type inequality for some mixing processes and dynamical systems with an application to learning
H Hang, I Steinwart
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