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ORCIDYu Yao 0005
Person information
- affiliation: University of Sydney, School of Computer Science, Sydney, Australia
- affiliation: Mohamed bin Zayed University of Artificial Intelligence, Department of Machine Learning, Masdar City, Abu Dhabi
- affiliation: Carnegie Mellon University, Pittsburgh, PA, USA
- affiliation (PhD 2023): University of Sydney, School of Computer Science, Sydney, Australia
Other persons with the same name
- Yao Yu (aka: Yu Yao) — disambiguation page
- Yu Yao 0001
![[0000-0002-7282-491X]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0002-7282-491X")
— Hainan University, School of Information and Communication Engineering, Haikou, China (and 3 more) - Yu Yao 0002 — Northeastern University, School of Computer Science and Engineering, Shenyang, China (and 1 more)
- Yu Yao 0003 — University of Plymouth, School of Engineering, Computing and Mathematics, Plymouth, UK (and 1 more)
- Yu Yao 0004 — Harbin Institute of Technology, School of Astronautics, Harbin, China (and 1 more)
- Yu Yao 0006 — University of Michigan, Robotics Institute, Ann Arbor, MI, USA
- Yu Yao 0007 — Southeast University, School of Electrical and Automation Engineering, Nanjing, China
- Yu Yao 0008 — Southeast University, School of Computer Science and Engineering, Key Laboratory of Computer Network and Information Integration, Nanjing, China (and 1 more)
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2020 – today
- 2024
[j2]Jialiang Shen, Yu Yao, Shaoli Huang, Zhiyong Wang, Jing Zhang, Ruxing Wang, Jun Yu, Tongliang Liu:
ProtoSimi: label correction for fine-grained visual categorization. Mach. Learn. 113(4): 1903-1920 (2024)- [c11]Lianyang Ma, Yu Yao, Tao Liang, Tongliang Liu:
Multi-scale Cooperative Multimodal Transformers for Multimodal Sentiment Analysis in Videos. AI (2) 2024: 281-297 - [c10]Huaming Chen, Jun Zhuang, Yu Yao, Wei Jin, Haohan Wang, Yong Xie, Chi-Hung Chi, Kim-Kwang Raymond Choo:
Trustworthy and Responsible AI for Information and Knowledge Management System. CIKM 2024: 5574-5576 - [c9]Ziming Hong, Zhenyi Wang, Li Shen, Yu Yao, Zhuo Huang, Shiming Chen, Chuanwu Yang, Mingming Gong, Tongliang Liu:
Improving Non-Transferable Representation Learning by Harnessing Content and Style. ICLR 2024 - [c8]Jiyang Zheng, Yu Yao, Bo Han, Dadong Wang, Tongliang Liu:
Enhancing Contrastive Learning for Ordinal Regression via Ordinal Content Preserved Data Augmentation. ICLR 2024 - [c7]Yexiong Lin, Yu Yao, Tongliang Liu:
Learning the Latent Causal Structure for Modeling Label Noise. NeurIPS 2024 - [i7]Weijie Tu, Weijian Deng, Dylan Campbell, Yu Yao, Jiyang Zheng, Tom Gedeon, Tongliang Liu:
Ranked from Within: Ranking Large Multimodal Models for Visual Question Answering Without Labels. CoRR abs/2412.06461 (2024) - 2023
- [j1]Yu Yao, Baosheng Yu, Chen Gong, Tongliang Liu:
Understanding How Pretraining Regularizes Deep Learning Algorithms. IEEE Trans. Neural Networks Learn. Syst. 34(9): 5828-5840 (2023) - [c6]Yu Yao, Mingming Gong, Yuxuan Du, Jun Yu, Bo Han, Kun Zhang, Tongliang Liu:
Which is Better for Learning with Noisy Labels: The Semi-supervised Method or Modeling Label Noise? ICML 2023: 39660-39673 - [c5]Wenjie Xuan, Shanshan Zhao, Yu Yao, Juhua Liu, Tongliang Liu, Yixin Chen, Bo Du, Dacheng Tao:
PNT-Edge: Towards Robust Edge Detection with Noisy Labels by Learning Pixel-level Noise Transitions. ACM Multimedia 2023: 1924-1932 - [c4]Yexiong Lin, Yu Yao, Xiaolong Shi, Mingming Gong, Xu Shen, Dong Xu, Tongliang Liu:
CS-Isolate: Extracting Hard Confident Examples by Content and Style Isolation. NeurIPS 2023 - [i6]Wenjie Xuan, Shanshan Zhao, Yu Yao, Juhua Liu, Tongliang Liu, Yixin Chen, Bo Du, Dacheng Tao:
PNT-Edge: Towards Robust Edge Detection with Noisy Labels by Learning Pixel-level Noise Transitions. CoRR abs/2307.14070 (2023) - 2022
- [c3]Yu Yao, Tongliang Liu, Bo Han, Mingming Gong, Gang Niu, Masashi Sugiyama, Dacheng Tao:
Rethinking Class-Prior Estimation for Positive-Unlabeled Learning. ICLR 2022 - [i5]Yexiong Lin, Yu Yao, Yuxuan Du, Jun Yu, Bo Han, Mingming Gong, Tongliang Liu:
Do We Need to Penalize Variance of Losses for Learning with Label Noise? CoRR abs/2201.12739 (2022) - [i4]Lianyang Ma, Yu Yao, Tao Liang, Tongliang Liu:
Multi-scale Cooperative Multimodal Transformers for Multimodal Sentiment Analysis in Videos. CoRR abs/2206.07981 (2022) - 2021
- [c2]Yu Yao, Tongliang Liu, Mingming Gong, Bo Han, Gang Niu, Kun Zhang:
Instance-dependent Label-noise Learning under a Structural Causal Model. NeurIPS 2021: 4409-4420 - [i3]Yu Yao, Tongliang Liu, Mingming Gong, Bo Han, Gang Niu, Kun Zhang:
Instance-dependent Label-noise Learning under a Structural Causal Model. CoRR abs/2109.02986 (2021) - 2020
- [c1]Yu Yao, Tongliang Liu, Bo Han, Mingming Gong, Jiankang Deng, Gang Niu, Masashi Sugiyama:
Dual T: Reducing Estimation Error for Transition Matrix in Label-noise Learning. NeurIPS 2020 - [i2]Yu Yao, Tongliang Liu, Bo Han, Mingming Gong, Gang Niu, Masashi Sugiyama, Dacheng Tao:
Towards Mixture Proportion Estimation without Irreducibility. CoRR abs/2002.03673 (2020) - [i1]Yu Yao, Tongliang Liu, Bo Han, Mingming Gong, Jiankang Deng, Gang Niu, Masashi Sugiyama:
Dual T: Reducing Estimation Error for Transition Matrix in Label-noise Learning. CoRR abs/2006.07805 (2020)
Coauthor Index
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