H. Wen BSc (Hongwei)

I started my Ph.D. in September 2021 under the supervision of Dr. Annika Betken and Dr. Hanyuan Hang. Before that, I got my B.S. degree in applied mathematics at Nankai University, China, and studied applied statistics as a postgraduate at the Renmin University of China. My research topic is on developing machine learning algorithms and establishing statistical learning theory for transfer learning and domain adaptation problems.

Engineering & Materials Science

# Experiments
# Labels
# Learning Algorithms
# Supervised Learning

Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS), Mathematics of Operations Research (MOR)

Preprints

H. Hang and H. Wen, Best-scored Random Forest Density Estimation, technical report, 2019. [preprint]

Published

H. Wen, J. Cui, H. Hang, J. Liu, Y. Wang, and Z. Lin, Leveraged Weighted Loss for Partial Label Learning, In Proceedings of the 38th International Conference on Machine Learning, PMLR 139:11091-11100, 2021 (Long Talk, Acceptance Rate 3%). [final]

H. Hang, Z. Lin, X. Liu, and H. Wen, Histogram Transform Ensembles for Large-scale Regression, Journal of Machine Learning Research, 22(95):1-87, 2021. [final]

Wen, H., Cui, J. , Hang, H., Liu, J., Wang, Y., & Lin, Z. (2021). Leveraged Weighted Loss for Partial Label Learning. In Proceedings of the 38th International Conference on Machine Learning (Proceedings of Machine Learning Research; Vol. 139). http://proceedings.mlr.press/v139/wen21a.html

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