Learning Intermediary Category Labels for Personal Recommendation. - Wenli Yu 002; Li Li 006; Jingyuan Wang; Dengbao Wang; Yong Wang; Zhanbo Yang; Min Huang (APWeb/WAIM (2), 2017)

Exploiting Label Correlations Using DBN Chains for Multi-Label Classification. - Dengbao Wang; Fei Hu 004; Li Li 006 (ChineseCSCW, 2017)

ProductRec: Product Bundle Recommendation Based on User's Sequential Patterns in Social Networking Service Environment. - Wenli Yu 002; Li Li 006; Xiaofei Xu; Dengbao Wang; Jingyuan Wang; Shiping Chen 001 (ICWS, 2017)

Extracting Label Importance Information for Multi-label Classification. - Dengbao Wang; Li Li 006; Jingyuan Wang; Fei Hu 004; Xiuzhen Zhang 001 (DASFAA (2), 2018)

A Deep Prediction Model of Traffic Flow Considering Precipitation Impact. - Jingyuan Wang; Fei Hu 004; Xiaofei Xu; Dengbao Wang; Li Li 006 (IJCNN, 2018)

A Locally Adaptive Multi-Label k-Nearest Neighbor Algorithm. - Dengbao Wang; Jingyuan Wang; Fei Hu 004; Li Li 006; Xiuzhen Zhang 001 (PAKDD (1), 2018)

Multi-View Multi-Label Learning with View-Specific Information Extraction. - Xuan Wu 003; Qing-Guo Chen; Yao Hu; Dengbao Wang; Xiaodong Chang; Xiaobo Wang; Min-Ling Zhang (IJCAI, 2019)

Learning from Noisy Labels with Complementary Loss Functions. - Deng-Bao Wang; Yong Wen; Lujia Pan; Min-Ling Zhang (AAAI, 2021)

Learning from Complementary Labels via Partial-Output Consistency Regularization. - Deng-Bao Wang; Lei Feng 006; Min-Ling Zhang (IJCAI, 2021)

Rethinking Calibration of Deep Neural Networks: Do Not Be Afraid of Overconfidence. - Deng-Bao Wang; Lei Feng 006; Min-Ling Zhang (NeurIPS, 2021)

Learning from Noisy Labels via Dynamic Loss Thresholding. - Hao Yang 015; Youzhi Jin; Ziyin Li; Deng-Bao Wang; Lei Miao; Xin Geng 001; Min-Ling Zhang (CoRR, 2021)

Revisiting Consistency Regularization for Deep Partial Label Learning. - Dong-Dong Wu; Deng-Bao Wang; Min-Ling Zhang (ICML, 2022)

Partial Label Learning with Gradually Induced Error-Correction Output Codes. - Yu-Xuan Shi; Deng-Bao Wang; Min-Ling Zhang (ICONIP (1), 2022)

Adaptive Graph Guided Disambiguation for Partial Label Learning. - Deng-Bao Wang; Min-Ling Zhang; Li Li 006 (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Partial-Label Regression. - Xin Cheng 007; Deng-Bao Wang; Lei Feng 006; Min-Ling Zhang; Bo An 001 (AAAI, 2023)

On the Pitfall of Mixup for Uncertainty Calibration. - Deng-Bao Wang; Lanqing Li; Peilin Zhao; Pheng-Ann Heng; Min-Ling Zhang (CVPR, 2023)

Distilling Reliable Knowledge for Instance-Dependent Partial Label Learning. - Dong-Dong Wu; Deng-Bao Wang; Min-Ling Zhang (AAAI, 2024)

Calibration Bottleneck: Over-compressed Representations are Less Calibratable. - Deng-Bao Wang; Min-Ling Zhang (ICML, 2024)

Dimensionality Reduction for Partial Label Learning: A Unified and Adaptive Approach. - Xiang-Ru Yu 001; Deng-Bao Wang; Min-Ling Zhang (IEEE Trans. Knowl. Data Eng., 2024)

Partial label learning with emerging new labels. - Xiang-Ru Yu 001; Deng-Bao Wang; Min-Ling Zhang (Mach. Learn., 2024)

Multiple-instance Learning from Triplet Comparison Bags. - Senlin Shu; Deng-Bao Wang; Suqin Yuan; Hongxin Wei; Jiuchuan Jiang; Lei Feng 006; Min-Ling Zhang (ACM Trans. Knowl. Discov. Data, 2024)

Student Loss: Towards the Probability Assumption in Inaccurate Supervision. - Shuo Zhang 030; Jianqing Li 002; Hamido Fujita; Yu-Wen Li 002; Deng-Bao Wang; Tingting Zhu 001; Min-Ling Zhang; Chengyu Liu 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Learning From Noisy Labels via Dynamic Loss Thresholding. - Hao Yang 015; Youzhi Jin; Ziyin Li; Deng-Bao Wang; Xin Geng 001; Min-Ling Zhang (IEEE Trans. Knowl. Data Eng., 2024)