吴国强，博士，副研究员，2012年本科毕业于山东大学，2015年和2019年分别硕士和博士毕业于中国科学院大学，2019-2021年在清华大学从事博士后研究工作。主要从事机器学习、优化、人工智能等方面的研究工作，尤其是统计学习理论以及多标签学习。在机器学习重要国际会议和期刊如ICML、NeurIPS、Neural Networks等录用或发表过多篇论文。长期担任机器学习重要期刊（如TPAMI）以及重要会议（如机器学习三大顶级会议ICML、NeurIPS、ICLR）的审稿人。
招生方向：
来源：软件工程、计算机科学、人工智能、数学、物理、自动化等
硕士生专业：软件工程；人工智能
研究方向：
机器学习
News:
2023/4/25. Two papers are accepted in ICML 2023. Congrats and thanks to all my co-authors.
2021/9/29. Three papers are accepted in NeurIPS 2021. Thanks to all my co-authors.
Guoqiang Wu, Chongxuan Li, Yilong Yin. Towards Understanding Generalization of Macro-AUC in Multi-label Learning, International Conference on Machine Learning (ICML) 2023
Chenyu Zheng, Guoqiang Wu, Fan Bao, Yue Cao, Chongxuan Li, Jun Zhu. Revisiting Discriminative vs. Generative Classifiers: Theory and Implications, International Conference on Machine Learning (ICML) 2023
Guoqiang Wu*, Chongxuan Li*, Kun Xu, and Jun Zhu. Rethinking and Reweighting the Univariate Losses for Multi-Label Ranking: Consistency and Generalization, Advances in Neural Information Processing Systems (NeurIPS) 2021 (* denotes equal contribution)
Fan Bao*, Guoqiang Wu*, Chongxuan Li*, Jun Zhu, and Bo Zhang. Stability and Generalization of Bilevel Programming in Hyperparameter Optimization, Advances in Neural Information Processing Systems (NeurIPS) 2021 (* denotes equal contribution)
Shuyu Cheng, Guoqiang Wu, and Jun Zhu. On the Convergence of Prior-Guided Zeroth-Order Optimization Algorithms, Advances in Neural Information Processing Systems (NeurIPS) 2021
Guoqiang Wu, and Jun Zhu. Multi-label classification: do Hamming loss and subset accuracy really conflict with each other? Advances in Neural Information Processing Systems (NeurIPS) 2020
Guoqiang Wu, Ruobing Zheng, Yingjie Tian and Dalian Liu. Joint ranking SVM and binary relevance with robust low-rank learning for multi-label classification, Neural Networks 2020
Guoqiang Wu, Yingjie Tian, and Dalian Liu. Cost-sensitive multi-label learning with positive and negative label pairwise correlations, Neural Networks 2018
Guoqiang Wu, Yingjie Tian, and Chunhua Zhang. A unified framework implementing linear binary relevance for multi-label learning, Neurocomputing 2018
Guoqiang Wu, Yingjie Tian, and Dalian Liu. Privileged Multi-Target Support Vector Regression, International Conference on Pattern Recognition (ICPR) 2018
