Hanyuan Hang

According to our database, Hanyuan Hang authored at least 26 papers between 2014 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

LLP-GAN: A GAN-Based Algorithm for Learning From Label Proportions.

Jiabin Liu, Bo Wang, Hanyuan Hang, Huadong Wang, Zhiquan Qi, Yingjie Tian, Yong Shi

IEEE Trans. Neural Networks Learn. Syst., November, 2023

GAN-CL: Generative Adversarial Networks for Learning From Complementary Labels.

Jiabin Liu, Hanyuan Hang, Bo Wang, Biao Li, Huadong Wang, Yingjie Tian, Yong Shi

IEEE Trans. Cybern., 2023

Class Probability Matching Using Kernel Methods for Label Shift Adaptation.

Hongwei Wen, Annika Betken, Hanyuan Hang

CoRR, 2023

Bagged Regularized k-Distances for Anomaly Detection.

Yuchao Cai, Yuheng Ma, Hanfang Yang, Hanyuan Hang

CoRR, 2023

2022

Under-bagging Nearest Neighbors for Imbalanced Classification.

Hanyuan Hang, Yuchao Cai, Hanfang Yang, Zhouchen Lin

J. Mach. Learn. Res., 2022

Bagged k-Distance for Mode-Based Clustering Using the Probability of Localized Level Sets.

Hanyuan Hang

CoRR, 2022

Random Forest Density Estimation.

Hongwei Wen, Hanyuan Hang

Proceedings of the International Conference on Machine Learning, 2022

2021

Histogram Transform Ensembles for Large-scale Regression.

Hanyuan Hang, Zhouchen Lin, Xiaoyu Liu, Hongwei Wen

J. Mach. Learn. Res., 2021

Local Adaptivity of Gradient Boosting in Histogram Transform Ensemble Learning.

Hanyuan Hang

CoRR, 2021

Gradient Boosted Binary Histogram Ensemble for Large-scale Regression.

Hanyuan Hang, Tao Huang, Yuchao Cai, Hanfang Yang, Zhouchen Lin

CoRR, 2021

Leveraged Weighted Loss for Partial Label Learning.

Hongwei Wen, Jingyi Cui, Hanyuan Hang, Jiabin Liu, Yisen Wang, Zhouchen Lin

Proceedings of the 38th International Conference on Machine Learning, 2021

GBHT: Gradient Boosting Histogram Transform for Density Estimation.

Jingyi Cui, Hanyuan Hang, Yisen Wang, Zhouchen Lin

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Matrix Infinitely Divisible Series: Tail Inequalities and Their Applications.

Chao Zhang, Xianjie Gao, Min-Hsiu Hsieh, Hanyuan Hang, Dacheng Tao

IEEE Trans. Inf. Theory, 2020

Boosted Histogram Transform for Regression.

Yuchao Cai, Hanyuan Hang, Hanfang Yang, Zhouchen Lin

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Attention-Based Pedestrian Attribute Analysis.

Zichang Tan, Yang Yang, Jun Wan, Hanyuan Hang, Guodong Guo, Stan Z. Li

IEEE Trans. Image Process., 2019

Histogram Transform Ensembles for Density Estimation.

Hanyuan Hang

CoRR, 2019

Density-based Clustering with Best-scored Random Forest.

Hanyuan Hang, Yuchao Cai, Hanfang Yang

CoRR, 2019

Best-scored Random Forest Classification.

Hanyuan Hang, Xiaoyu Liu, Ingo Steinwart

CoRR, 2019

Best-scored Random Forest Density Estimation.

Hanyuan Hang, Hongwei Wen

CoRR, 2019

Two-stage Best-scored Random Forest for Large-scale Regression.

Hanyuan Hang, Yingyi Chen, Johan A. K. Suykens

CoRR, 2019

2018

Kernel Density Estimation for Dynamical Systems.

Hanyuan Hang, Ingo Steinwart, Yunlong Feng, Johan A. K. Suykens

J. Mach. Learn. Res., 2018

Optimal Learning with Anisotropic Gaussian SVMs.

Hanyuan Hang, Ingo Steinwart

CoRR, 2018

Matrix Infinitely Divisible Series: Tail Inequalities and Applications in Optimization.

Chao Zhang, Xianjie Gao, Min-Hsiu Hsieh, Hanyuan Hang, Dacheng Tao

CoRR, 2018

2016

Learning Theory Estimates with Observations from General Stationary Stochastic Processes.

Hanyuan Hang, Yunlong Feng, Ingo Steinwart, Johan A. K. Suykens

Neural Comput., 2016

Kernelized Elastic Net Regularization: Generalization Bounds, and Sparse Recovery.

Yunlong Feng, Shao-Gao Lv, Hanyuan Hang, Johan A. K. Suykens

Neural Comput., 2016

2014

Fast learning from α-mixing observations.

Hanyuan Hang, Ingo Steinwart

J. Multivar. Anal., 2014