Ms Sarah Monazam Erfani

  • Room: Level: 07 Room: 14
  • Building: Doug McDonell Building
  • Campus: Parkville

Research interests

  • Big Data (Scalable Learning, Data Integration, Data Analysis)
  • Computer Security & Privacy (Cybersecurity, Data Privacy)
  • Data Mining
  • Machine Learning

Biography

Sarah Erfani is a lecturer in the Department of Computing and Information Systems at The University of Melbourne. Research interests: - Machine Learning - Large-scale Data Mining - Cyber Security - Data Privacy

Recent publications

  1. Moshtaghi M, Monazam Erfani S, Leckie C, Bezdek JC. Exponentially Weighted Ellipsoidal Model for Anomaly Detection. International Journal of Intelligent Systems. John Wiley & Sons. 2017.
  2. Monazam Erfani S, Baktashmotlagh, Moshtaghi, Nguyen, Leckie, Bailey, Kotagiri. From Shared Subspaces to Shared Landmarks: A Robust Multi-Source Classification Approach. 31st AAAI Conference on Artificial Intelligence (AAAI). 2017.
  3. Lyu L, Law YW, Monazam Erfani S, Leckie C, Palaniswami M. An Improved Scheme for Privacy-Preserving Collaborative Anomaly Detection. 2016 IEEE INTERNATIONAL CONFERENCE ON PERVASIVE COMPUTING AND COMMUNICATION WORKSHOPS (PERCOM WORKSHOPS). IEEE. 2016.
  4. Ghafoori Z, Monazam Erfani S, Rajasegarar S, Karunasekera S, Leckie C. Anomaly detection in non-stationary data: Ensemble based self-adaptive OCSVM. International Joint Conference on Neural Networks (IJCNN). 2016, Vol. 2016-October.
  5. Monazam Erfani S, Rajasegarar S, Leckie C. High-dimensional and large-scale anomaly detection using a linear one-class SVM with deep learning. PATTERN RECOGNITION. Pergamon-Elsevier Science. 2016, Vol. 58.
  6. Timothy Glennan, , Christopher Leckie, Leckie C, Monazam Erfani S. Improved classification of known and unknown network traffic flows using semi-supervised machine learning. 21st Australasian Conference on Information Security and Privacy (ACISP). Springer Verlag. 2016, Vol. 9723. Editors: Liu JK, Steinfeld R.
  7. Monazam Erfani S, Baktashmotlagh M, Rajasegarar S, Nguyen V, Leckie C, Bailey J, Kotagiri R. R1STM: One-class support tensor machine with randomised kernel. 16th SIAM International Conference on Data Mining 2016, SDM 2016. 2016.
  8. Monazam Erfani S, Baktashmotlagh M, Moshtaghi M, Nguyen V, Leckie C, Bailey J, Kotagiri R. Robust domain generalisation by enforcing distribution invariance. 25th International Joint Conference on Artificial Intelligence (IJCAI). 2016, Vol. 2016-January.
  9. Amsaleg L, Bailey J, Monazam Erfani S, Furon T, Houle ME, Radovanović M, Nguyen X. The vulnerability of learning to adversarial perturbation increases with intrinsic dimensionality. NII Technical Reports. 2016, Issue 5.
  10. Nguyen X, Monazam Erfani S, Paisitkriangkrai S, Bailey J, Leckie C, Kotagiri R. Training Robust Models with Random Projection. International Conference on Pattern Recognition. 2016.
  11. Ghafoori Z, Rajasegarar S, Monazam Erfani S, Karunasekera S, Leckie C. Unsupervised Parameter Estimation for One-Class Support Vector Machines. 20th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD). Springer Verlag. 2016, Vol. 9652. Editors: Bailey J, Khan L, Washio T, Dobbie G, Huang JZ, Wang R.
  12. Monazam Erfani S, Baktashmotlagh M, Rajasegarar S, Karunasekera S, Leckie C. R1SVM: A randomised nonlinear approach to large-scale anomaly detection. Proceedings of the National Conference on Artificial Intelligence. 2015, Vol. 1.