Yunwen Lei

Dr.

Accepting PhD Students

PhD projects

Machine Learning, Statistical Learning Theory, Optimization

20152022

Research activity per year

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Personal profile

Research interests

My research interests lie in the areas of machine learning and learning theory, with emphasis on the following topics: online learning, deep learning, optimization and extreme classification. In particular, I am interested in developing and analyzing scalable optimization methods for large-scale learning problems.

Education/Academic qualification

Doctor of Engineering, Wuhan University

1 Sep 200830 Jun 2014

Award Date: 30 Jun 2014

Bachelor of Science, Hunan University

1 Sep 200430 Jun 2008

Award Date: 30 Jun 2008

Keywords

  • TA Engineering (General). Civil engineering (General)
  • Computer Science
  • Machine Learning

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  • Noise-efficient learning of differentially private partitioning machine ensembles: noise reduction in private forests

    Huang, Z., Lei, Y. & Kaban, A., 14 Jun 2022, (Accepted/In press) European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Amin, M-R., Canu, S., Fischer, A., Guns, T., Novak, P. K. & Tsoumakas, G. (eds.). Springer, (A Springer Nature Computer Science book series (CCIS, LNAI, LNBI, LNBIP or LNCS).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Open Access
    File
    15 Downloads (Pure)
  • On the generalization analysis of adversarial learning

    Mustafa, W., Lei, Y. & Kloft, M., 12 Jul 2022, International Conference on Machine Learning, 17-23 July 2022, Baltimore, Maryland, USA. Chaudhuri, K., Jegelka, S., Song, L., Szepesvari, C., Niu, G. & Sabato, S. (eds.). Proceedings of Machine Learning Research, p. 16174-16196 23 p. (Proceedings of Machine Learning Research; vol. 162).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Open Access
    File
    8 Downloads (Pure)
  • Fine-grained generalization analysis of inductive matrix completion

    Ledent, A., Alves, R., Lei, Y. & Kloft, M., 1 Dec 2021, Advances in Neural Information Processing Systems 34. Ranzato, M., Beygelzimer, A., Liang, P. S., Vaughan, J. W. & Dauphin, Y. (eds.). NeurIPS, (Advances in neural information processing systems).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Open Access
    File
    12 Downloads (Pure)
  • Fine-grained generalization analysis of vector-valued learning

    Wu, L., Ledent, A., Lei, Y. & Kloft, M., 18 May 2021, AAAI'21 Proceedings of the Thirty-fifth AAAI Conference on Artificial Intelligence. AAAI Press, p. 10338-10346 9 p. (Proceedings of the AAAI Conference on Artificial Intelligence; vol. 35, no. 12).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Open Access
    File
    75 Downloads (Pure)
  • Generalization guarantee of SGD for pairwise learning

    Lei, Y., Liu, M. & Ying, Y., 1 Dec 2021, Advances in Neural Information Processing Systems 34. Ranzato, M., Beygelzimer, A., Liang, P. S., Vaughan, J. W. & Dauphin, Y. (eds.). NeurIPS, (Advances in neural information processing systems).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Open Access
    File
    15 Downloads (Pure)