Congyu Qiao

According to our database, Congyu Qiao authored at least 14 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Variational Label Enhancement for Instance-Dependent Partial Label Learning.

Ning Xu, Congyu Qiao, Yuchen Zhao, Xin Geng, Min-Ling Zhang

IEEE Trans. Pattern Anal. Mach. Intell., December, 2024

Reduction-based Pseudo-label Generation for Instance-dependent Partial Label Learning.

Congyu Qiao, Ning Xu, Yihao Hu, Xin Geng

CoRR, 2024

ULAREF: A Unified Label Refinement Framework for Learning with Inaccurate Supervision.

Congyu Qiao, Ning Xu, Yihao Hu, Xin Geng

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Aligned Objective for Soft-Pseudo-Label Generation in Supervised Learning.

Ning Xu, Yihao Hu, Congyu Qiao, Xin Geng

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Variational Label-Correlation Enhancement for Congestion Prediction.

Biao Liu, Congyu Qiao, Ning Xu, Xin Geng, Ziran Zhu, Jun Yang

Proceedings of the 29th Asia and South Pacific Design Automation Conference, 2024

2023

Multi-View Partial Multi-Label Learning via Graph-Fusion-Based Label Enhancement.

Ning Xu, Yong-Di Wu, Congyu Qiao, Yi Ren, Minxue Zhang, Xin Geng

IEEE Trans. Knowl. Data Eng., November, 2023

FREDIS: A Fusion Framework of Refinement and Disambiguation for Unreliable Partial Label Learning.

Congyu Qiao, Ning Xu, Jiaqi Lv, Yi Ren, Xin Geng

Proceedings of the International Conference on Machine Learning, 2023

Progressive Purification for Instance-Dependent Partial Label Learning.

Ning Xu, Biao Liu, Jiaqi Lv, Congyu Qiao, Xin Geng

Proceedings of the International Conference on Machine Learning, 2023

Decompositional Generation Process for Instance-Dependent Partial Label Learning.

Congyu Qiao, Ning Xu, Xin Geng

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Decomposition-based Generation Process for Instance-Dependent Partial Label Learning.

Congyu Qiao, Ning Xu, Xin Geng

CoRR, 2022

One Positive Label is Sufficient: Single-Positive Multi-Label Learning with Label Enhancement.

Ning Xu, Congyu Qiao, Jiaqi Lv, Xin Geng, Min-Ling Zhang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Instance-Dependent Partial Label Learning.

Ning Xu, Congyu Qiao, Xin Geng, Min-Ling Zhang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

BGGAN: Bokeh-Glass Generative Adversarial Network for Rendering Realistic Bokeh.

Ming Qian, Congyu Qiao, Jiamin Lin, Zhenyu Guo, Chenghua Li, Cong Leng, Jian Cheng

Proceedings of the Computer Vision - ECCV 2020 Workshops, 2020

AIM 2020 Challenge on Rendering Realistic Bokeh.

Andrey Ignatov, Radu Timofte, Ming Qian, Congyu Qiao, Jiamin Lin, Zhenyu Guo, Chenghua Li, Cong Leng, Jian Cheng, Juewen Peng, Xianrui Luo, Ke Xian, Zijin Wu, Zhiguo Cao, Densen Puthussery, C. V. Jiji, Hrishikesh P. S, Melvin Kuriakose, Saikat Dutta, Sourya Dipta Das, Nisarg A. Shah, Kuldeep Purohit, Praveen Kandula, Maitreya Suin, A. N. Rajagopalan, Saagara M. B, Minnu A. L, Sanjana A. R, Praseeda S, Ge Wu, Xueqin Chen, Tengyao Wang, Max Zheng, Hulk Wong, Jay Zou

Proceedings of the Computer Vision - ECCV 2020 Workshops, 2020