Projects per year
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).
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 level. Dive into details by clicking on the dots.
Projects 2018 2020
- 3 Active
Towards Robust Learning Systems via Amortized Optimization and Domain Adaptation
Le, T., Phung, D., Xiang, Y., Zhang, J., Erfani, S., Rubinstein, B., Leckie, C., Nock, R. & Knight, K.
15/04/19 → 14/04/20
Project: Research
Cardiorespiratory function as a non-invasive biomarker for detecting seizures with artificial intelligence: Utilising data from long-term patient recordings from an epilepsy monitoring unit
O'Brien, T., Kwan, P., Sivathamboo, S., Perucca, P., Ge, Z., Le, T., Phung, D., Bonnington, P. & Piccenna, L.
8/04/19 → 8/04/20
Project: Research
Deep Learning for Cyber (Data61 CRP 38)
Phung, D., Le, T., Xiang, Y., Zhang, J., Wen, S., Murray, T. & Nock, R.
15/06/18 → 30/06/20
Project: Research
Research Output 2009 2019
GoGP: scalable geometric-based Gaussian process for online regression
Le, T., Nguyen, K., Nguyen, V., Nguyen, T. D. & Phung, D., 20 Jul 2019, In : Knowledge and Information Systems. p. 197-226 30 p.Research output: Contribution to journal › Article › Research › peer-review
Maximal divergence sequential auto-encoder for binary software vulnerability detection*
Le, T., Nguyen, T., Le, T., Phung, D., Montague, P., De Vel, O. & Qu, L., 2019, The Seventh International Conference on Learning Representations. Levine, S., Livescu, K. & Mohamed, S. (eds.). La Jolla CA USA: OpenReview, 15 p.Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
Open Access
File
Robust anomaly detection in videos using multilevel representations
Vu, H., Nguyen, T. D., Le, T., Luo, W. & Phung, D., 2019, Proceedings of AAAI19-Thirty-Third AAAI conference on Artificial Intelligence. Van Hentenryck, P. & Zhou, Z-H. (eds.). Palo Alto CA USA: Association for the Advancement of Artificial Intelligence (AAAI), p. 5216-5223 8 p. 2579. (Proceedings of the AAAI Conference on Artificial Intelligence; vol. 33, no. 1).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
Open Access
File
Batch Normalized Deep Boltzmann Machines
Vu, H., Nguyen, T. D., Le, T., Luo, W. & Phung, D., 2018, Proceedings of Asian Conference on Machine Learning 2018. Zhu, J. & Takeuchi, I. (eds.). USA: Proceedings of Machine Learning Research (PMLR), p. 359-374 16 p. (Proceedings of Machine Learning Research; vol. 95).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
Open Access
File
Bayesian Multi-Hyperplane Machine for pattern recognition
Nguyen, K., Le, T., Nguyen, T. D. & Phung, D., 2018, 2018 24th International Conference on Pattern Recognition (ICPR): Aug. 20 2018 to Aug. 24 2018 Beijing, China. Liu, C-L., Chellappa, R. & Pietikäinen, M. (eds.). Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, p. 609-614 6 p. 8545139Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research
Prizes
The first prize of Imagine Cup 2010 Australia round
Trung Le (Recipient), 2010
Prize: Prize (including medals and awards)