Wu, Guoqiang

15 publications

ICML 2025 A Theory for Conditional Generative Modeling on Multiple Data Sources Rongzhen Wang, Yan Zhang, Chenyu Zheng, Chongxuan Li, Guoqiang Wu
ICLRW 2025 A Theory for Conditional Generative Modeling on Multiple Data Sources Rongzhen Wang, Yan Zhang, Chenyu Zheng, Chongxuan Li, Guoqiang Wu
AAAI 2025 Towards Macro-AUC Oriented Imbalanced Multi-Label Continual Learning Yan Zhang, Guoqiang Wu, Bingzheng Wang, Teng Pang, Haoliang Sun, Yilong Yin
TMLR 2024 Calibrating Deep Ensemble Through Functional Variational Inference Zhijie Deng, Feng Zhou, Jianfei Chen, Guoqiang Wu, Jun Zhu
AAAI 2024 DiffAIL: Diffusion Adversarial Imitation Learning Bingzheng Wang, Guoqiang Wu, Teng Pang, Yan Zhang, Yilong Yin
NeurIPS 2024 Lower Bounds of Uniform Stability in Gradient-Based Bilevel Algorithms for Hyperparameter Optimization Rongzhen Wang, Chenyu Zheng, Guoqiang Wu, Xu Min, Xiaolu Zhang, Jun Zhou, Chongxuan Li
NeurIPS 2024 On Mesa-Optimization in Autoregressively Trained Transformers: Emergence and Capability Chenyu Zheng, Wei Huang, Rongzhen Wang, Guoqiang Wu, Jun Zhu, Chongxuan Li
ACML 2023 Can Infinitely Wide Deep Nets Help Small-Data Multi-Label Learning? Guoqiang Wu, Jun Zhu
ICML 2023 Revisiting Discriminative vs. Generative Classifiers: Theory and Implications Chenyu Zheng, Guoqiang Wu, Fan Bao, Yue Cao, Chongxuan Li, Jun Zhu
NeurIPS 2023 Toward Understanding Generative Data Augmentation Chenyu Zheng, Guoqiang Wu, Chongxuan Li
ICML 2023 Towards Understanding Generalization of Macro-AUC in Multi-Label Learning Guoqiang Wu, Chongxuan Li, Yilong Yin
NeurIPS 2021 On the Convergence of Prior-Guided Zeroth-Order Optimization Algorithms Shuyu Cheng, Guoqiang Wu, Jun Zhu
NeurIPS 2021 Rethinking and Reweighting the Univariate Losses for Multi-Label Ranking: Consistency and Generalization Guoqiang Wu, Chongxuan Li, Kun Xu, Jun Zhu
NeurIPS 2021 Stability and Generalization of Bilevel Programming in Hyperparameter Optimization Fan Bao, Guoqiang Wu, Chongxuan Li, Jun Zhu, Bo Zhang
NeurIPS 2020 Multi-Label Classification: Do Hamming Loss and Subset Accuracy Really Conflict with Each Other? Guoqiang Wu, Jun Zhu