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Personal profile

Biography

My research involves both theoretical and practical aspects. More specifically, this focuses on deep generative models, kernel methods, optimization in machine learning and Bayesian inference whose gained theories can be applied to  supervised learning, semi-supervised learning, adversarial learning, online learning, anomaly detection, and cyber security. I have published in the top-notch conferences and high quality journals in machine learning, artificial intelligence, and data mining including NIPS, ICLR, AISTATS, UAI, IJCAI, ICDM and Journal of Machine Learning Research (JMLR).

Education/Academic qualification

Computer Science, Doctor of Philosophy, University of Canberra

Award Date: 27 Mar 2013

Research area keywords

  • Deep Generative Models
  • Optimisation for Machine Learning
  • Kernel Methods
  • Online Learning
  • Deep Learning for Cyber Security
  • Anomaly Detection

Network

Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
  • Code Action Network for binary function scope identification

    Nguyen, V., Le, T., Le, T., Nguyen, K., de Vel, O., Montague, P., Grundy, J. & Phung, D., 2020, Advances in Knowledge Discovery and Data Mining: 24th Pacific-Asia Conference, PAKDD 2020 Singapore, May 11–14, 2020 Proceedings, Part I. Lauw, H. W., Wong, R. C-W., Ntoulas, A., Lim, E-P., Ng, S-K. & Pan, S. J. (eds.). Cham Switzerland: Springer, p. 712-725 14 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12084 LNAI).

    Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

    Open Access
    File
  • Code Pointer Network for binary function scope identification

    Nguyen, V., Le, T., Nguyen, K., de Vel, O., Montague, P. & Phung, DI., 2020, 2020 International Joint Conference on Neural Networks (IJCNN), 2020 Conference Proceedings2020 International Joint Conference on Neural Networks, IJCNN 2020 - Proceedings. Roy, A. (ed.). Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, 7 p. 9207293

    Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

  • Deep Cost-Sensitive Kernel Machine for binary software vulnerability detection

    Nguyen, T., Le, T., Nguyen, K., de Vel, O., Montague, P., Grundy, J. & Phung, D., 2020, Advances in Knowledge Discovery and Data Mining: 24th Pacific-Asia Conference, PAKDD 2020 Singapore, May 11–14, 2020 Proceedings, Part II. Lauw, H. W., Wong, R. C-W., Lim, E-P., Ntoulas, A., Ng, S-K. & Pan, S. J. (eds.). Cham Switzerland: Springer, p. 164-177 14 p. (Lecture Notes in Computer Science; vol. 12085 ).

    Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

    Open Access
    File
    1 Citation (Scopus)
  • Dual-component deep domain adaptation: a new approach for cross project software vulnerability detection

    Nguyen, V., Le, T., de Vel, O., Montague, P., Grundy, J. & Phung, D., 2020, Advances in Knowledge Discovery and Data Mining: 24th Pacific-Asia Conference, PAKDD 2020 Singapore, May 11–14, 2020 Proceedings, Part I. Lauw, H. W., Wong, R. C-W., Ntoulas, A., Lim, E-P., Ng, S-K. & Pan, S. J. (eds.). Cham Switzerland: Springer, p. 699-711 13 p. (Lecture Notes in Computer Science ; vol. 12084 ).

    Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

    Open Access
  • Improving adversarial robustness by enforcing local and global compactness

    Bui, A., Le, T., Zhao, H., Montague, P., deVel, O., Abraham, T. & Phung, D., 2020, Computer Vision – ECCV 2020 : 16th European Conference Glasgow, UK, August 23–28, 2020 Proceedings, Part XXVII. Vedaldi, A., Bischof, H., Brox, T. & Frahm, J-M. (eds.). Cham Switzerland : Springer, p. 209-223 15 p. (Lecture Notes in Computer Science ; vol. 12372 ).

    Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review