I started my Ph.D. in January 2023 under the supervision of Dr. Hanyuan Hang. Before that, I received a B.S. degree in Statistics in 2018 and studied statistics as a postgraduate at Renmin University of China. My current research interests lie in developing statistical learning theory framework of machine learning algorithms including ensemble learning and weakly-supervised learning algorithms.
J. Cui, T. Huang, H. Hang, Y. Wang, J. Kwok, Leveraged Asymmetric Loss with Disambiguation for Multi-label Recognition with One-Positive Annotations, technical report, 2022. [preprint]
H. Hang, T. Huang, Y. Cai, H. Yang, and Z. Lin, Gradient Boosted Binary Histogram Ensemble for Large-scale Regression, technical report, 2021. [preprint]
T. Huang, S. Li, X. Jia, H. Lu, J. Liu, Neighbor2Neighbor: A Self-Supervised Framework for Deep Image Denoising, IEEE Transactions on Image Processing, 2022. [final]
T. Huang, S. Li, X. Jia, H. Lu, J. Liu, Neighbor2Neighbor: Self-Supervised Denoising from Single Noisy Image, In IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2021. [final]