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Xiaobo Xia
Xiaobo Xia
Ph.D. student, The University of Sydney
Verified email at uni.sydney.edu.au - Homepage
Title
Cited by
Cited by
Year
Are anchor points really indispensable in label-noise learning?
X Xia, T Liu, N Wang, B Han, C Gong, G Niu, M Sugiyama
NeurIPS 2019, 2019
3672019
Part-dependent label noise: Towards instance-dependent label noise
X Xia, T Liu, B Han, N Wang, M Gong, H Liu, G Niu, D Tao, M Sugiyama
NeurIPS 2020 (spotlight), 2020
2692020
Robust early-learning: Hindering the memorization of noisy labels
X Xia, T Liu, B Han, C Gong, N Wang, Z Ge, Y Chang
ICLR 2021, 2021
2542021
Selective-supervised contrastive learning with noisy labels
S Li, X Xia, S Ge, T Liu
CVPR 2022, 2022
1792022
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
ICLR 2022, 2022
1122022
Class2Simi: A noise reduction perspective on learning with noisy labels
S Wu, X Xia, T Liu, B Han, M Gong, N Wang, H Liu, G Niu
ICML 2021, 2021
692021
Extended T: Learning with mixed closed-set and open-set noisy labels
X Xia, B Han, N Wang, J Deng, J Li, Y Mao, T Liu
TPAMI 2023, 2023
492023
Estimating noise transition matrix with label correlations for noisy multi-label learning
S Li, X Xia, H Zhang, Y Zhan, S Ge, T Liu
NeurIPS 2022 (spotlight), 2022
482022
Learning lightweight super-resolution networks with weight pruning
X Jiang, N Wang, J Xin, X Xia, X Yang, X Gao
Neural Network 2021, 2021
482021
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
ICLR 2023, 2023
462023
Objects in semantic topology
S Yang, P Sun, Y Jiang, X Xia, R Zhang, Z Yuan, C Wang, P Luo, M Xu
ICLR 2022, 2022
322022
Harnessing out-of-distribution examples via augmenting content and style
Z Huang, X Xia, L Shen, B Han, M Gong, C Gong, T Liu
ICLR 2023, 2023
302023
HumanMAC: Masked motion completion for human motion prediction
L Chen, J Zhang, Y Li, Y Pang, X Xia, T Liu
ICCV 2023, 2023
272023
Robust generalization against photon-limited corruptions via worst-case sharpness minimization
Z Huang, M Zhu, X Xia, L Shen, J Yu, C Gong, B Han, B Du, T Liu
CVPR 2023, 2023
232023
Combating noisy labels with sample selection by mining high-discrepancy examples
X Xia, B Han, Y Zhan, J Yu, M Gong, C Gong, T Liu
ICCV 2023, 2023
182023
A holistic view of label noise transition matrix in deep learning and beyond
LIN Yong, R Pi, W Zhang, X Xia, J Gao, X Zhou, T Liu, B Han
ICLR 2023, 2023
18*2023
Out-of-distribution detection with an adaptive likelihood ratio on informative hierarchical vae
Y Li, C Wang, X Xia, T Liu, X Miao, B An
NeurIPS 2022, 2022
152022
One shot learning as instruction data prospector for large language models
Y Li, B Hui, X Xia, J Yang, M Yang, L Zhang, S Si, J Liu, T Liu, F Huang, ...
ACL 2024, 2024
14*2024
IDEAL: Influence-driven selective annotations empower in-context learners in large language models
S Zhang, X Xia, Z Wang, L Chen, J Liu, Q Wu, T Liu
ICLR 2024, 2024
132024
LR-SVM+: Learning using privileged information with noisy labels
Z Wu, X Xia, R Wang, J Li, J Yu, Y Mao, T Liu
TMM 2021, 2021
132021
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