Dengbao Wang

According to our database, Dengbao Wang authored at least 19 papers between 2017 and 2024.

Collaborative distances:

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

2024

Multiple-instance Learning from Triplet Comparison Bags.

Senlin Shu, Deng-Bao Wang, Suqin Yuan, Hongxin Wei, Jiuchuan Jiang, Lei Feng, Min-Ling Zhang

ACM Trans. Knowl. Discov. Data, May, 2024

Partial label learning with emerging new labels.

Xiang-Ru Yu, Deng-Bao Wang, Min-Ling Zhang

Mach. Learn., April, 2024

Distilling Reliable Knowledge for Instance-Dependent Partial Label Learning.

Dong-Dong Wu, Deng-Bao Wang, Min-Ling Zhang

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

On the Pitfall of Mixup for Uncertainty Calibration.

Deng-Bao Wang, Lanqing Li, Peilin Zhao, Pheng-Ann Heng, Min-Ling Zhang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Partial-Label Regression.

Xin Cheng, Deng-Bao Wang, Lei Feng, Min-Ling Zhang, Bo An

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Adaptive Graph Guided Disambiguation for Partial Label Learning.

Deng-Bao Wang, Min-Ling Zhang, Li Li

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Partial Label Learning with Gradually Induced Error-Correction Output Codes.

Yu-Xuan Shi, Deng-Bao Wang, Min-Ling Zhang

Proceedings of the Neural Information Processing - 29th International Conference, 2022

Revisiting Consistency Regularization for Deep Partial Label Learning.

Dong-Dong Wu, Deng-Bao Wang, Min-Ling Zhang

Proceedings of the International Conference on Machine Learning, 2022

2021

Learning from Noisy Labels via Dynamic Loss Thresholding.

Hao Yang, Youzhi Jin, Ziyin Li, Deng-Bao Wang, Lei Miao, Xin Geng, Min-Ling Zhang

CoRR, 2021

Rethinking Calibration of Deep Neural Networks: Do Not Be Afraid of Overconfidence.

Deng-Bao Wang, Lei Feng, Min-Ling Zhang

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

Learning from Complementary Labels via Partial-Output Consistency Regularization.

Deng-Bao Wang, Lei Feng, Min-Ling Zhang

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Learning from Noisy Labels with Complementary Loss Functions.

Deng-Bao Wang, Yong Wen, Lujia Pan, Min-Ling Zhang

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2019

Multi-View Multi-Label Learning with View-Specific Information Extraction.

Xuan Wu, Qing-Guo Chen, Yao Hu, Dengbao Wang, Xiaodong Chang, Xiaobo Wang, Min-Ling Zhang

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

2018

A Locally Adaptive Multi-Label k-Nearest Neighbor Algorithm.

Dengbao Wang, Jingyuan Wang, Fei Hu, Li Li, Xiuzhen Zhang

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2018

A Deep Prediction Model of Traffic Flow Considering Precipitation Impact.

Jingyuan Wang, Fei Hu, Xiaofei Xu, Dengbao Wang, Li Li

Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Extracting Label Importance Information for Multi-label Classification.

Dengbao Wang, Li Li, Jingyuan Wang, Fei Hu, Xiuzhen Zhang

Proceedings of the Database Systems for Advanced Applications, 2018

2017

ProductRec: Product Bundle Recommendation Based on User's Sequential Patterns in Social Networking Service Environment.

Wenli Yu, Li Li, Xiaofei Xu, Dengbao Wang, Jingyuan Wang, Shiping Chen

Proceedings of the 2017 IEEE International Conference on Web Services, 2017

Exploiting Label Correlations Using DBN Chains for Multi-Label Classification.

Dengbao Wang, Fei Hu, Li Li

Proceedings of the 12th Chinese Conference on Computer Supported Cooperative Work and Social Computing, 2017

Learning Intermediary Category Labels for Personal Recommendation.

Wenli Yu, Li Li, Jingyuan Wang, Dengbao Wang, Yong Wang, Zhanbo Yang, Min Huang

Proceedings of the Web and Big Data - First International Joint Conference, 2017