Address: J12/ 1 Cleveland St, Darlington, NSW 2008, Australia
I am a third-year bachelor-straight-to-Ph.D. student at the School of Computer Science, The University of Sydney. My research focuses on learning with noisy labels, generative models, and causal discovery. I was a recipient of the Google Ph.D. Fellowship in 2022.
Ph.D. student, 2021.03 - 2024.09 (expected) The University of Sydney, Australia, advised by Prof. Tongliang Liu
B.Eng., 2016.09 - 2020.06 Xidian University, Xi'an, China, advised by Prof. Nannan Wang
HumanMAC: Masked Motion Completion for Human Motion Prediction
L. Chen*, J. Zhang*, Y. Li, Y. Pan, X. Xia✉, T. Liu
Moderate Coreset: A Universal Method of Data Selection for Real-world Data-efficient Deep Learning
X. Xia, J. Liu, J. Yu, X. Shen, B. Han, T. Liu
Pluralistic Image Completion with Gaussian Mixture Models
X. Xia*, W. Yang*, J. Ren, Y. Li, Y. Zhan, B. Han, T. Liu
Sample-Efficient Kernel Mean Estimator with Marginalized Corrupted Data
X. Xia*, S. Shan*, M. Gong, N. Wang, F. Gao, H. Wei, T. Liu
Sample Selection with Uncertainty of Losses for Learning with Noisy Labels
X. Xia, T. Liu, B. Han, M. Gong, J. Yu, G. Niu, M. Sugiyama
Robust Early-learning: Hindering the Memorization of Noisy Labels
X. Xia, T. Liu, B. Han, C. Gong, N. Wang, Z. Ge, Y. Chang
Part-dependent Label Noise: Towards Instance-dependent Label Noise [Spotlight]
X. Xia, T. Liu, B. Han, N. Wang, M. Gong, H. Liu, G. Niu, D. Tao, M. Sugiyama
Are Anchor Points Really Indispensable in Label-noise Learning?
X. Xia, T. Liu, N. Wang, B. Han, C. Gong, G. Niu, M. Sugiyama
Google Ph.D. Fellowship in Machine Learning, 2022.
ICML Outstanding Reviewer Award, 2022.
NeurIPS Outstanding Reviewer Award, 2021.
Chinese National Scholarship, 2019.
Conference Reviewer: NeurIPS, ICML, ICLR, AISTATS, UAI, CVPR, ICCV, ECCV, SIGKDD, AAAI, IJCAI, etc.
Journal Reviewer: TMLR, MLJ, TKDE, TNN, etc.
|© Xiaobo Xia | Last update: August 2023|