Yu Yao
Yu Yao
Lecturer in the University of Sydney
Verified email at - Homepage
Cited by
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Dual t: Reducing estimation error for transition matrix in label-noise learning
Y Yao, T Liu, B Han, M Gong, J Deng, G Niu, M Sugiyama
NeurIPS, 2020
Instance-dependent label-noise learning under a structural causal model
Y Yao, T Liu, M Gong, B Han, G Niu, K Zhang
NeurIPS, 2021
Rethinking class-prior estimation for positive-unlabeled learning
Y Yao, T Liu, B Han, M Gong, G Niu, M Sugiyama, D Tao
ICLR, 2022
Multi-scale cooperative multimodal transformers for multimodal sentiment analysis in videos
L Ma, Y Yao, T Liang, T Liu
arXiv preprint arXiv:2206.07981, 2022
Causality Encourages the Identifiability of Instance-Dependent Label Noise
Y Yao, T Liu, M Gong, B Han, G Niu, K Zhang
Machine Learning for Causal Inference, 2023
Understanding how pretraining regularizes deep learning algorithms
Y Yao, B Yu, C Gong, T Liu
Which is Better for Learning with Noisy Labels: The Semi-supervised Method or Modeling Label Noise?
Y Yao, M Gong, Y Du, J Yu, B Han, K Zhang, T Liu
ICML, 2023
StarmapVis: An interactive and narrative visualisation tool for single-cell and spatial data
S Ma, X Fang, Y Yao, J Li, DC Morgan, Y Xia, CSM Kwok, MCK Lo, ...
Computational and Structural Biotechnology Journal 21, 1598-1605, 2023
Enhancing Contrastive Learning for Ordinal Regression via Ordinal Content Preserved Data Augmentation
J Zheng, Y Yao, B Han, D Wang, T Liu
ICLR, 2024
PNT-Edge: Towards Robust Edge Detection with Noisy Labels by Learning Pixel-level Noise Transitions
W Xuan, S Zhao, Y Yao, J Liu, T Liu, Y Chen, B Du, D Tao
ACM Multimedia, 2023
ProtoSimi: label correction for fine-grained visual categorization
J Shen, Y Yao, S Huang, Z Wang, J Zhang, R Wang, J Yu, T Liu
Machine Learning, 1-18, 2023
Improving Non-Transferable Representation Learning by Harnessing Content and Style
Z Hong, Z Wang, L Shen, Y Yao, Z Huang, S Chen, C Yang, M Gong, ...
ICLR (spotlight), 2024
CS-Isolate: Extracting Hard Confident Examples by Content and Style Isolation
Y Lin, Y Yao, X Shi, M Gong, X Shen, D Xu, T Liu
NeurIPS, 2023
Do We Need to Penalize Variance of Losses for Learning with Label Noise?
Y Lin, Y Yao, Y Du, J Yu, B Han, M Gong, T Liu
arXiv preprint arXiv:2201.12739, 2022
Can Label-Noise Transition Matrix Help to Improve Sample Selection and Label Correction?
Y Yao, X Li, T Liu, A Blair, M Gong, B Han, G Niu, M Sugiyama
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