教师简介

吴国强,副研究员,硕士生导师,泰山学者青年专家(免答辩),入选山东大学青年学者未来计划,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。在机器学习重要国际会议和期刊如ICMLNeurIPS、Neural Networks等发表过多篇论文。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。


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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


欢迎对机器学习感兴趣的数学与英语能力强的同学与我联系。


软件工程:学硕(2024秋入学,剩余1个名额),专硕(2024秋入学,剩余1个名额)

人工智能:学硕(2024秋入学,剩余1个名额),专硕(2024秋入学,剩余1个名额)


欢迎2024级保研同学邮件与我联系。


研究方向:

机器学习



News:

2023/12/9.  One paper is acceted in AAAI 2024. Congrats to Bingzheng, Teng Pang and Yan Zhang.

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.


论文列表(* indicates equal contribution and † indicates correspondence.)

2023

    • Guoqiang Wu, Chongxuan Li, Yilong Yin. Towards Understanding Generalization of Macro-AUC in Multi-label Learning, International Conference on Machine Learning (ICML) 2023 (CCF-A)

    • 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 (CCF-A)

    • Chenyu Zheng, Guoqiang Wu, Chongxuan Li†. Toward Understanding Generative Data Augmentation, Advances in Neural Information Processing Systems (NeurIPS) 2023 (CCF-A)

    • Bingzheng Wang, Guoqiang Wu, Teng Pang, Yan Zhang, Yilong Yin. DiffAIL: Diffusion Adversarial Imitation Learning, AAAI Conference on Artificial Intelligence (AAAI)  (CCF-A)

    • Guoqiang Wu, Jun Zhu. Can Infinitely Wide Deep Nets Help Small-data Multi-label Learning? Asian Conference on Machine Learning (ACML) 2023  (CCF-C)

2021

    • 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  (CCF-A)

    • 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 (CCF-A)

    • 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 (CCF-A)

2020

    • 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 (CCF-A)

    • 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 (中科院SCI一区,CCF-B)

2018

    • Guoqiang Wu, Yingjie Tian, and Dalian Liu.  Cost-sensitive multi-label learning with positive and negative label pairwise correlations, Neural Networks 2018 (中科院SCI一区,CCF-B)

    • Guoqiang Wu, Yingjie Tian, and Chunhua Zhang. A unified framework implementing linear binary relevance for multi-label learning, Neurocomputing 2018 (中科院SCI二区,CCF-C)

    • Guoqiang Wu, Yingjie Tian, and Dalian Liu. Privileged Multi-Target Support Vector Regression, International Conference on Pattern Recognition (ICPR) 2018 (CCF-C)


教育经历
  • 2008-9 — 2012-6
    山东大学
    软件工程
    工学学士学位
  • 2012-9 — 2015-6
    中国科学院大学
    计算机软件与理论
    工学硕士学位
  • 2016-9 — 2019-6
    中国科学院大学
    计算机应用技术
    工学博士学位
工作经历
  • 2019-7 — 2021-7
     清华大学计算机系 
    博士后
论文
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