Christopher Leckie

System and Process for Managing Network Traffic

T PENG, C LECKIE, R KOTAGIRI

METEOR: Learning Memory and Time Efficient Representations from Multi-modal Data Streams

A Silva, S Karunasekera, C Leckie, L Luo

Conference Proceedings  |  2020  |  Proceedings of the 29th ACM International Conference on Information & Knowledge Management

Many learning tasks involve multi-modal data streams, where continuous data from different modes convey a comprehensive descriptio..

Adversarial Reinforcement Learning under Partial Observability in Autonomous Computer Network Defence

Yi Han, David Hubczenko, Paul Montague, Olivier De Vel, Tamas Abraham, Benjamin IP Rubinstein, Christopher Leckie, Tansu Alpcan, Sarah Erfani

Conference Proceedings  |  2020  |  2020 International Joint Conference on Neural Networks (IJCNN)

Recent studies have demonstrated that reinforcement learning (RL) agents are susceptible to adversarial manipulation, similar to v..

Discovery of contrast corridors from trajectory data in heterogeneous dynamic cellular networks

Li Li, Sarah Erfani, Chien Aun Chan, Christopher Leckie

Conference Proceedings  |  2020  |  2020 International Joint Conference on Neural Networks (IJCNN)

In 5G networks, the deployment and management of mobile edge computing infrastructure is a major challenge for mobile operators. M..

Improving Single and Multi-View Blockmodelling by Algebraic Simplification

R Ramteke, PJ Stuckey, J Chan, K Ramamohanarao, J Bailey, C Leckie, E Demirovic

Conference Proceedings  |  2020  |  2020 International Joint Conference on Neural Networks (IJCNN)

Blockmodelling is an important technique in social network analysis for discovering the latent structures and groupings in graphs...

Evaluation of Centralised vs Distributed Collaborative Intrusion Detection Systems in Multi-Access Edge Computing

R Sharma, CA Chan, C Leckie

Conference Proceedings  |  2020  |  IFIP Networking 2020 Conference and Workshops, Networking 2020

LN-SNE: Log-Normal Distributed Stochastic Neighbor Embedding for Anomaly Detection

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

Journal article  |  2020  |  IEEE Transactions on Knowledge and Data Engineering

We present a new unsupervised dimensionality reduction technique, called LN-SNE, for anomaly detection. LN-SNE generates a paramet..

Exploiting patterns to explain individual predictions

Y Jia, J Bailey, K Ramamohanarao, C Leckie, X Ma

Journal article  |  2020  |  Knowledge and Information Systems

Users need to understand the predictions of a classifier, especially when decisions based on the predictions can have severe conse..

Multi-spatial Scale Event Detection from Geo-tagged Tweet Streams via Power-law Verification

Y Han, S Karunasekera, C Leckie, A Harwood

Conference Proceedings  |  2020  |  2019 IEEE International Conference on Big Data (Big Data)

Compared with traditional news media, social media nowadays provides a richer and more timely source of news. We are interested in..

USTAR: Online Multimodal Embedding for Modeling User-Guided Spatiotemporal Activity

Amila Silva, Shanika Karunasekera, Chris Leckie, Ling Luo

Conference Proceedings  |  2020  |  2019 IEEE International Conference on Big Data (Big Data)

Building spatiotemporal activity models for people's activities in urban spaces is important for understanding the ever-increasing..

Unsupervised online change point detection in high-dimensional time series

M Zameni, A Sadri, Z Ghafoori, M Moshtaghi, FD Salim, C Leckie, K Ramamohanarao

Journal article  |  2020  |  Knowledge and Information Systems

A critical problem in time series analysis is change point detection, which identifies the times when the underlying distribution ..