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2020 – today
- 2024
[c5]Hongwei Wen, Annika Betken, Hanyuan Hang:
Class Probability Matching with Calibrated Networks for Label Shift Adaption. ICLR 2024- 2023
- [j10]Jiabin Liu
, Hanyuan Hang, Bo Wang, Biao Li, Huadong Wang, Yingjie Tian, Yong Shi:
GAN-CL: Generative Adversarial Networks for Learning From Complementary Labels. IEEE Trans. Cybern. 53(1): 236-247 (2023) - [j9]Jiabin Liu, Bo Wang, Hanyuan Hang, Huadong Wang, Zhiquan Qi, Yingjie Tian, Yong Shi:
LLP-GAN: A GAN-Based Algorithm for Learning From Label Proportions. IEEE Trans. Neural Networks Learn. Syst. 34(11): 8377-8388 (2023) - [i17]Yuchao Cai, Yuheng Ma, Hanfang Yang, Hanyuan Hang:
Bagged Regularized k-Distances for Anomaly Detection. CoRR abs/2312.01046 (2023) - [i16]Hongwei Wen, Annika Betken, Hanyuan Hang:
Class Probability Matching Using Kernel Methods for Label Shift Adaptation. CoRR abs/2312.07282 (2023) - 2022
- [j8]Hanyuan Hang, Yuchao Cai, Hanfang Yang, Zhouchen Lin:
Under-bagging Nearest Neighbors for Imbalanced Classification. J. Mach. Learn. Res. 23: 118:1-118:63 (2022) - [c4]Hongwei Wen, Hanyuan Hang:
Random Forest Density Estimation. ICML 2022: 23701-23722 - [i15]Hanyuan Hang:
Bagged k-Distance for Mode-Based Clustering Using the Probability of Localized Level Sets. CoRR abs/2210.09786 (2022) - 2021
- [j7]Hanyuan Hang, Zhouchen Lin, Xiaoyu Liu, Hongwei Wen:
Histogram Transform Ensembles for Large-scale Regression. J. Mach. Learn. Res. 22: 95:1-95:87 (2021) - [c3]Jingyi Cui, Hanyuan Hang, Yisen Wang, Zhouchen Lin:
GBHT: Gradient Boosting Histogram Transform for Density Estimation. ICML 2021: 2233-2243 - [c2]Hongwei Wen, Jingyi Cui, Hanyuan Hang, Jiabin Liu, Yisen Wang, Zhouchen Lin:
Leveraged Weighted Loss for Partial Label Learning. ICML 2021: 11091-11100 - [i14]Hanyuan Hang, Tao Huang, Yuchao Cai, Hanfang Yang, Zhouchen Lin:
Gradient Boosted Binary Histogram Ensemble for Large-scale Regression. CoRR abs/2106.01986 (2021) - [i13]Hongwei Wen, Jingyi Cui, Hanyuan Hang, Jiabin Liu, Yisen Wang, Zhouchen Lin:
Leveraged Weighted Loss for Partial Label Learning. CoRR abs/2106.05731 (2021) - [i12]Jingyi Cui, Hanyuan Hang, Yisen Wang, Zhouchen Lin:
GBHT: Gradient Boosting Histogram Transform for Density Estimation. CoRR abs/2106.05738 (2021) - [i11]Hanyuan Hang, Yuchao Cai, Hanfang Yang, Zhouchen Lin:
Under-bagging Nearest Neighbors for Imbalanced Classification. CoRR abs/2109.00531 (2021) - [i10]Hanyuan Hang:
Local Adaptivity of Gradient Boosting in Histogram Transform Ensemble Learning. CoRR abs/2112.02589 (2021) - 2020
- [j6]Chao Zhang, Xianjie Gao, Min-Hsiu Hsieh, Hanyuan Hang, Dacheng Tao:
Matrix Infinitely Divisible Series: Tail Inequalities and Their Applications. IEEE Trans. Inf. Theory 66(2): 1099-1117 (2020) - [c1]Yuchao Cai, Hanyuan Hang, Hanfang Yang, Zhouchen Lin:
Boosted Histogram Transform for Regression. ICML 2020: 1251-1261
2010 – 2019
- 2019
- [j5]Zichang Tan, Yang Yang, Jun Wan, Hanyuan Hang, Guodong Guo, Stan Z. Li:
Attention-Based Pedestrian Attribute Analysis. IEEE Trans. Image Process. 28(12): 6126-6140 (2019) - [i9]Hanyuan Hang, Yingyi Chen, Johan A. K. Suykens:
Two-stage Best-scored Random Forest for Large-scale Regression. CoRR abs/1905.03438 (2019) - [i8]Hanyuan Hang, Hongwei Wen:
Best-scored Random Forest Density Estimation. CoRR abs/1905.03729 (2019) - [i7]Hanyuan Hang, Xiaoyu Liu, Ingo Steinwart:
Best-scored Random Forest Classification. CoRR abs/1905.11028 (2019) - [i6]Hanyuan Hang, Yuchao Cai, Hanfang Yang:
Density-based Clustering with Best-scored Random Forest. CoRR abs/1906.10094 (2019) - [i5]Hanyuan Hang:
Histogram Transform Ensembles for Density Estimation. CoRR abs/1911.11581 (2019) - [i4]Hanyuan Hang, Zhouchen Lin, Xiaoyu Liu, Hongwei Wen:
Histogram Transform Ensembles for Large-scale Regression. CoRR abs/1912.04738 (2019) - 2018
- [j4]Hanyuan Hang, Ingo Steinwart, Yunlong Feng, Johan A. K. Suykens:
Kernel Density Estimation for Dynamical Systems. J. Mach. Learn. Res. 19: 35:1-35:49 (2018) - [i3]Chao Zhang, Xianjie Gao, Min-Hsiu Hsieh, Hanyuan Hang, Dacheng Tao:
Matrix Infinitely Divisible Series: Tail Inequalities and Applications in Optimization. CoRR abs/1809.00781 (2018) - [i2]Hanyuan Hang, Ingo Steinwart:
Optimal Learning with Anisotropic Gaussian SVMs. CoRR abs/1810.02321 (2018) - 2016
- [j3]Yunlong Feng, Shao-Gao Lv, Hanyuan Hang, Johan A. K. Suykens:
Kernelized Elastic Net Regularization: Generalization Bounds, and Sparse Recovery. Neural Comput. 28(3): 525-562 (2016) - [j2]Hanyuan Hang, Yunlong Feng, Ingo Steinwart, Johan A. K. Suykens:
Learning Theory Estimates with Observations from General Stationary Stochastic Processes. Neural Comput. 28(12): 2853-2889 (2016) - [i1]Hanyuan Hang, Yunlong Feng, Ingo Steinwart, Johan A. K. Suykens:
Learning theory estimates with observations from general stationary stochastic processes. CoRR abs/1605.02887 (2016) - 2014
- [j1]Hanyuan Hang, Ingo Steinwart:
Fast learning from α-mixing observations. J. Multivar. Anal. 127: 184-199 (2014)
Coauthor Index
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