Sarah Monazam Erfani

Support vector machines resilient against training data integrity attacks

S Weerasinghe, SM Erfani, T Alpcan, C Leckie

Journal article  |  2019  |  Pattern Recognition

Support Vector Machines (SVMs) are vulnerable to integrity attacks, where malicious attackers distort the training data in order t..

Multi-scale trajectory clustering to identify corridors in mobile networks

L Li, CA Chan, S Erfani, C Leckie

Conference Proceedings  |  2019  |  Proceedings of the 28th ACM International Conference on Information and Knowledge Management

Distributed nonlinear model predictive control and reinforcement learning

I Saeed, T Alpcan, SM Erfani, MB Yilmaz

Conference Proceedings  |  2019  |  2019 Australian & New Zealand Control Conference (ANZCC)

Robust and Accurate Short-Term Load Forecasting: A Cluster Oriented Ensemble Learning Approach

F Fahiman, SM Erfani, C Leckie

Conference Proceedings  |  2019  |  2019 International Joint Conference on Neural Networks (IJCNN)

One of the most critical tasks for operating a power system is load forecasting in order to keep balance between demand and supply..

Deep Learning and One-class SVM based Anomalous Crowd Detection

M Yang, S Rajasegarar, SM Erfani, C Leckie

Conference Proceedings  |  2019  |  2019 International Joint Conference on Neural Networks (IJCNN)

Anomalous event detection in videos is an important and challenging task. This paper proposes a deep representation approach to th..

MMF: Attribute Interpretable Collaborative Filtering

Y Su, SM Erfani, R Zhang

Conference Proceedings  |  2019  |  2019 International Joint Conference on Neural Networks (IJCNN)

Collaborative filtering is one of the most popular techniques in designing recommendation systems, and its most representative mod..

Adaptive Edge Caching based on Popularity and Prediction for Mobile Networks

L Li, CA Chan, S Erfani, C Leckie

Conference Proceedings  |  2019  |  2019 International Joint Conference on Neural Networks (IJCNN)

Edge caching in mobile networks can improve users' experience, reduce latency and balance the network traffic load. However, edge ..

Data-Driven Dynamic Probabilistic Reserve Sizing Based on Dynamic Bayesian Belief Networks

Fateme Fahiman, Steven Disano, Sarah Monazam Erfani, Pierluigi Mancarella, Christopher Leckie

Journal article  |  2019  |  IEEE Transactions on Power Systems

Online cluster validity indices for performance monitoring of streaming data clustering

Masud Moshtaghi, James C Bezdek, Sarah M Erfani, Christopher Leckie, James Bailey

Journal article  |  2019  |  International Journal of Intelligent Systems

Detection of Anomalous Communications with SDRs and Unsupervised Adversarial Learning

S Weerasinghe, SM Erfani, T Alpcan, C Leckie, J Riddle

Conference Proceedings  |  2019  |  2018 IEEE 43rd Conference on Local Computer Networks (LCN)

© 2018 IEEE. Software-defined radios (SDRs) with substantial cognitive (computing) and networking capabilities provide an opportun..

SynthNet: Learning to synthesize music end-to-end

F Schimbinschi, C Walder, SM Erfani, J Bailey

Conference Proceedings  |  2019  |  Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence

We consider the problem of learning a mapping directly from annotated music to waveforms, bypassing traditional single note synthe..

Continuous Evaluation of Video Lectures from Real-Time Difficulty Self-Report

Namrata Srivastava, Eduardo Velloso, Jason M Lodge, Sarah Erfani, James Bailey

Conference Proceedings  |  2019  |  Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems - CHI '19

With the increased reach and impact of video lectures, it is crucial to understand how they are experienced. Whereas previous stud..

Online CP Decomposition for Sparse Tensors

S Zhou, S Erfani, J Bailey

Conference Proceedings  |  2018  |  2018 IEEE International Conference on Data Mining (ICDM)

© 2018 IEEE. Tensor decomposition techniques such as CANDECOMP/PARAFAC (CP) decomposition have achieved great success across a ran..

Efficient Unsupervised Parameter Estimation for One-Class Support Vector Machines

Zahra Ghafoori, Sarah M Erfani, Sutharshan Rajasegarar, James C Bezdek, Shanika Karunasekera, Christopher Leckie

Journal article  |  2018  |  IEEE Transactions on Neural Networks and Learning Systems

Dimensionality-Driven Learning with Noisy Labels

X Ma, Yisen Wang, Michael E Houle, Shuo Zhou, Sarah M Erfani, Shu-tao Xia, Sudanthi Wijewickrema, James Bailey

Conference Proceedings  |  2018  |  35th International Conference on Machine Learning, ICML 2018

Datasets with significant proportions of noisy (incorrect) class labels present challenges for training accurate Deep Neural Netwo..

Ensemble Fuzzy Clustering Using Cumulative Aggregation on Random Projections

Punit Rathore, James C Bezdek, Sarah M Erfani, Sutharshan Rajasegarar, Marimuthu Palaniswami

Journal article  |  2018  |  IEEE Transactions on Fuzzy Systems

Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality

X Ma, Bo Li, Yisen Wang, Sarah M. Erfani, Sudanthi Wijewickrema, Grant Schoenebeck, Dawn Song, Michael E Houle, james Bailey

Conference Proceedings  |  2018  |  6th International Conference on Learning Representations, ICLR 2018 - Conference Track Proceedings

Deep Neural Networks (DNNs) have recently been shown to be vulnerable against adversarial examples, which are carefully crafted in..

The vulnerability of learning to adversarial perturbation increases with intrinsic dimensionality

L Amsaleg, J Bailey, D Barbe, S Erfani, ME Houle, V Nguyen, M Radovanovic

Conference Proceedings  |  2018  |  2017 IEEE Workshop on Information Forensics and Security (WIFS)

© 2017 IEEE. Recent research has shown that machine learning systems, including state-of-the-art deep neural networks, are vulnera..

Unsupervised Adversarial Anomaly Detection using One-Class Support Vector Machines

T Alpcan, Prameesha Weerasinghe, Margreta Kuijper, Sarah Monazam Erfani, Christopher Leckie

Conference Proceedings  |  2018

Anomaly detection discovers regular patterns in unlabeled data and identifies the non-conforming data points, which in some cases ..

Deep learning based game-theoretical approach to evade jamming attacks

S Weerasinghe, T Alpcan, SM Erfani, C Leckie, P Pourbeik, J Riddle

Conference Proceedings  |  2018  |  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Reinforcement learning for autonomous defence in software-defined networking

Y Han, BIP Rubinstein, T Abraham, T Alpcan, O De Vel, S Erfani, D Hubczenko, C Leckie, P Montague

Conference Proceedings  |  2018  |  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

© 2018, Springer Nature Switzerland AG. Despite the successful application of machine learning (ML) in a wide range of domains, ad..

Predicting complex activities from ongoing multivariate time series

W Cheng, S Erfani, R Zhang, K Ramamohanarao

Conference Proceedings  |  2018  |  IJCAI International Joint Conference on Artificial Intelligence

© 2018 International Joint Conferences on Artificial Intelligence. All right reserved. The rapid development of sensor networks en..

Learning Deep Hidden Nonlinear Dynamics from Aggregate Data

Yisen Wang, Bo Dai, Lingkai Kong, Sarah Monazam Erfani, James Bailey, Hongyuan Zha

Conference Proceedings  |  2018  |  34th Conference on Uncertainty in Artificial Intelligence 2018, UAI 2018

© 2018 by Association For Uncertainty in Artificial Intelligence (AUAI) All rights reserved. Learning nonlinear dynamics from diff..

Learning Datum-Wise Sampling Frequency for Energy-Efficient Human Activity Recognition

Weihao Cheng, Sarah Erfani, Rui Zhang, Kotagiri Ramamohanarao

Conference Proceedings  |  2018  |  THIRTY-SECOND AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTIETH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE / EIGHTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE

Markov dynamic subsequence ensemble for energy-efficient activity recognition

W Cheng, S Erfani, R Zhang, K Ramamohanarao

Conference Proceedings  |  2017  |  Proceedings of the 14th EAI International Conference on Mobile and Ubiquitous Systems Computing Networking and Services

Exponentially Weighted Ellipsoidal Model for Anomaly Detection

M Moshtaghi, SM Erfani, C Leckie, JC Bezdek

Journal article  |  2017  |  International Journal of Intelligent Systems (IJIS)

The Vulnerability of Learning to Adversarial Perturbation Increases with Intrinsic Dimensionality

Laurent Amsaleg, James Bailey, Dominique Barbe, Sarah Erfani, Michael E Houle, Nguyen Vinh, Milos Radovanovic

Journal article  |  2017  |  NII Technical Reports

Summarizing Significant Changes in Network Traffic Using Contrast Pattern Mining

Elaheh Alipour Chavary, Sarah M Erfani, Christopher Leckie

Conference Proceedings  |  2017  |  Proceedings of the 2017 ACM on Conference on Information and Knowledge Management - CIKM '17

A Pattern Tree based Method for Mining Conditional Contrast Patterns of Multi-Source Data

Li Li, Sarah Erfani, Christopher Leckie

Conference Proceedings  |  2017  |  2017 IEEE International Conference on Data Mining Workshops (ICDMW)

Improving Load Forecasting Based on Deep Learning and K-shape Clustering

Fateme Fahiman, Sarah M Erfani, Sutharshan Rajasegarar, Marimuthu Palaniswami, Christopher Leckie

Conference Proceedings  |  2017  |  2017 International Joint Conference on Neural Networks (IJCNN)

SCED: A General Framework for Sparse Tensor Decomposition with Constraints and Elementwise Dynamic Learning

Shuo Zhou, Sarah M Erfani, James Bailey

Conference Proceedings  |  2017  |  2017 IEEE International Conference on Data Mining (ICDM)

Accurate recognition of the current activity in the presence of multiple activities

W Cheng, S Erfani, R Zhang, R Kotagiri

Conference Proceedings  |  2017  |  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

© 2017, Springer International Publishing AG. Sensor based activity recognition (AR) has gained extensive attention in recent year..

From Shared Subspaces to Shared Landmarks: A Robust Multi-Source Classification Approach

S MONAZAM ERFANI, undefined Baktashmotlagh, undefined moshtaghi, undefined Nguyen, undefined leckie, undefined bailey, undefined kotagiri

Conference Proceedings  |  2017  |  31st AAAI Conference on Artificial Intelligence, AAAI 2017

An Efficient Visual Assessment of Cluster Tendency Tool for Large-scale Time Series Data Sets

Timothy B Iredale, Sarah M Erfani, Christopher Leckie

Conference Proceedings  |  2017  |  2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

Fuzzy c-Shape: A new algorithm for clustering finite time series waveforms

Fateme Fahiman, James C Bezdek, Sarah M Erfani, Marimuthu Palaniswami, Christopher Leckie

Conference Proceedings  |  2017  |  2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

Robust Domain Generalisation by Enforcing Distribution Invariance

S MONAZAM ERFANI, M Baktashmotlagh, M Moshtaghi, X Nguyen, C Leckie, J Bailey, K Ramamohanarao

Conference Proceedings  |  2016  |  IJCAI International Joint Conference on Artificial Intelligence

An Improved Scheme for Privacy-Preserving Collaborative Anomaly Detection

Lingjuan Lyu, Yee Wei Law, Sarah M Erfani, Christopher Leckie, Marimuthu Palaniswami

Conference Proceedings  |  2016  |  2016 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops)

R1STM: One-class support tensor machine with randomised kernel

SM Erfani, M Baktashmotlagh, S Rajasegarar, V Nguyen, C Leckie, J Bailey, K Ramamohanarao

Conference Proceedings  |  2016  |  16th SIAM International Conference on Data Mining 2016, SDM 2016

Unsupervised Parameter Estimation for One-Class Support Vector Machines

Zahra Ghafoori, Sutharshan Rajasegarar, Sarah M Erfani, Shanika Karunasekera, Christopher A Leckie

Conference Proceedings  |  2016  |  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Anomaly Detection in Non-stationary Data: Ensemble based Self-Adaptive OCSVM

Zahra Ghafoori, Sarah M Erfani, Sutharshan Rajasegarar, Shanika Karunasekera, Christopher A Leckie

Conference Proceedings  |  2016  |  2016 International Joint Conference on Neural Networks (IJCNN)

Training Robust Models with Random Projection

XV Nguyen, S Monazam Erfani, S Paisitkriangkrai, J Bailey, C Leckie, K Ramamohanarao

Conference Proceedings  |  2016  |  2016 23rd International Conference on Pattern Recognition (ICPR)

Improved classification of known and unknown network traffic flows using semi-supervised machine learning

T Glennan, C Leckie, SM Erfani

Conference Proceedings  |  2016  |  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

High-Dimensional and Large-Scale Anomaly Detection using a Linear One-Class SVM with Deep Learning

S MONAZAM ERFANI, S Rajasegarar, S Karunasekera, C Leckie

Journal article  |  2016  |  Pattern Recognition

R1SVM: A Randomised Nonlinear Approach to Large-Scale Anomaly Detection

Sarah M Erfani, Mahsa Baktashmotlagh, Sutharshan Rajasegarar, Shanika Karunasekera, Chris Leckie

Conference Proceedings  |  2015  |  Twenty-Ninth AAAI Conference on Artificial Intelligence

Privacy-preserving collaborative anomaly detection for participatory sensing

SM Erfani, YW Law, S Karunasekera, CA Leckie, M Palaniswami

Conference Proceedings  |  2014  |  Advances in Knowledge Discovery and Data Mining

Privacy-Preserving Data Aggregation in Participatory Sensing Networks

S MONAZAM ERFANI, SA Karunasekera, CA Leckie, U Parampalli

Conference Proceedings  |  2013  |  IEEE ISSNIP: Sensing the Future

An efficient approach to detecting concept-evolution in network data streams

SM Erfani, S Rajasegarar, C Leckie

Conference Proceedings  |  2011  |  Australasian Telecommunication Networks and Applications Conference (ATNAC), 2011