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Dengbao Wang
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2020 – today
- 2024
- [j5]Xiang-Ru Yu, Deng-Bao Wang, Min-Ling Zhang
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Partial label learning with emerging new labels. Mach. Learn. 113(4): 1549-1565 (2024) - [j4]Shuo Zhang
Student Loss: Towards the Probability Assumption in Inaccurate Supervision. IEEE Trans. Pattern Anal. Mach. Intell. 46(6): 4460-4475 (2024) - [j3]Senlin Shu
Multiple-instance Learning from Triplet Comparison Bags. ACM Trans. Knowl. Discov. Data 18(4): 90:1-90:18 (2024) - [j2]Hao Yang
Learning From Noisy Labels via Dynamic Loss Thresholding. IEEE Trans. Knowl. Data Eng. 36(11): 6503-6516 (2024) - [c17]Dong-Dong Wu, Deng-Bao Wang, Min-Ling Zhang:
Distilling Reliable Knowledge for Instance-Dependent Partial Label Learning. AAAI 2024: 15888-15896 - [c16]Deng-Bao Wang, Min-Ling Zhang:
Calibration Bottleneck: Over-compressed Representations are Less Calibratable. ICML 2024 - 2023
- [c15]Xin Cheng
Partial-Label Regression. AAAI 2023: 7140-7147 - [c14]Deng-Bao Wang, Lanqing Li, Peilin Zhao, Pheng-Ann Heng, Min-Ling Zhang:
On the Pitfall of Mixup for Uncertainty Calibration. CVPR 2023: 7609-7618 - [i2]Xin Cheng, Deng-Bao Wang, Lei Feng, Min-Ling Zhang, Bo An:
Partial-Label Regression. CoRR abs/2306.08968 (2023) - 2022
- [j1]Deng-Bao Wang
Adaptive Graph Guided Disambiguation for Partial Label Learning. IEEE Trans. Pattern Anal. Mach. Intell. 44(12): 8796-8811 (2022) - [c13]Dong-Dong Wu, Deng-Bao Wang, Min-Ling Zhang:
Revisiting Consistency Regularization for Deep Partial Label Learning. ICML 2022: 24212-24225 - [c12]Yu-Xuan Shi, Deng-Bao Wang, Min-Ling Zhang:
Partial Label Learning with Gradually Induced Error-Correction Output Codes. ICONIP (1) 2022: 200-211 - 2021
- [c11]Deng-Bao Wang, Yong Wen, Lujia Pan, Min-Ling Zhang:
Learning from Noisy Labels with Complementary Loss Functions. AAAI 2021: 10111-10119 - [c10]Deng-Bao Wang, Lei Feng, Min-Ling Zhang:
Learning from Complementary Labels via Partial-Output Consistency Regularization. IJCAI 2021: 3075-3081 - [c9]Deng-Bao Wang, Lei Feng, Min-Ling Zhang:
Rethinking Calibration of Deep Neural Networks: Do Not Be Afraid of Overconfidence. NeurIPS 2021: 11809-11820 - [i1]Hao Yang, Youzhi Jin, Ziyin Li, Deng-Bao Wang, Lei Miao, Xin Geng, Min-Ling Zhang:
Learning from Noisy Labels via Dynamic Loss Thresholding. CoRR abs/2104.02570 (2021)
2010 – 2019
- 2019
- [c8]Xuan Wu, Qing-Guo Chen, Yao Hu, Dengbao Wang, Xiaodong Chang, Xiaobo Wang, Min-Ling Zhang
Multi-View Multi-Label Learning with View-Specific Information Extraction. IJCAI 2019: 3884-3890 - [c7]Deng-Bao Wang, Li Li, Min-Ling Zhang
Adaptive Graph Guided Disambiguation for Partial Label Learning. KDD 2019: 83-91 - 2018
- [c6]Dengbao Wang, Li Li, Jingyuan Wang, Fei Hu, Xiuzhen Zhang:
Extracting Label Importance Information for Multi-label Classification. DASFAA (2) 2018: 424-439 - [c5]Jingyuan Wang, Fei Hu, Xiaofei Xu, Dengbao Wang, Li Li:
A Deep Prediction Model of Traffic Flow Considering Precipitation Impact. IJCNN 2018: 1-7 - [c4]Dengbao Wang, Jingyuan Wang, Fei Hu, Li Li, Xiuzhen Zhang:
A Locally Adaptive Multi-Label k-Nearest Neighbor Algorithm. PAKDD (1) 2018: 81-93 - 2017
- [c3]Wenli Yu, Li Li, Jingyuan Wang, Dengbao Wang, Yong Wang, Zhanbo Yang, Min Huang:
Learning Intermediary Category Labels for Personal Recommendation. APWeb/WAIM (2) 2017: 124-132 - [c2]Dengbao Wang, Fei Hu, Li Li:
Exploiting Label Correlations Using DBN Chains for Multi-Label Classification. ChineseCSCW 2017: 145-152 - [c1]Wenli Yu, Li Li, Xiaofei Xu, Dengbao Wang, Jingyuan Wang, Shiping Chen
ProductRec: Product Bundle Recommendation Based on User's Sequential Patterns in Social Networking Service Environment. ICWS 2017: 301-308
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last updated on 2024-10-23 20:34 CEST by the dblp team
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