Wang, Deng-Bao

10 publications

IJCAI 2025 Wrapped Partial Label Dimensionality Reduction via Dependence Maximization Xiang-Ru Yu, Deng-Bao Wang, Min-Ling Zhang

ICML 2024 Calibration Bottleneck: Over-Compressed Representations Are Less Calibratable Deng-Bao Wang, Min-Ling Zhang

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

MLJ 2024 Partial Label Learning with Emerging New Labels Xiang-Ru Yu, Deng-Bao Wang, Min-Ling Zhang

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

AAAI 2023 Partial-Label Regression Xin Cheng, Deng-Bao Wang, Lei Feng, Min-Ling Zhang, Bo An

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

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

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

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