Network Anomaly Detection Using a Commute Distance Based Approach. - Nguyen Lu Dang Khoa; Tahereh Babaie; Sanjay Chawla; Zainab R. Zaidi (ICDM Workshops, 2010)

Robust Outlier Detection Using Commute Time and Eigenspace Embedding. - Nguyen Lu Dang Khoa; Sanjay Chawla (PAKDD (2), 2010)

Online Anomaly Detection Systems Using Incremental Commute Time - Nguyen Lu Dang Khoa; Sanjay Chawla (CoRR, 2011)

Large Scale Spectral Clustering Using Approximate Commute Time Embedding - Nguyen Lu Dang Khoa; Sanjay Chawla (CoRR, 2011)

Large Scale Spectral Clustering Using Resistance Distance and Spielman-Teng Solvers. - Nguyen Lu Dang Khoa; Sanjay Chawla (Discovery Science, 2012)

On Damage Identification in Civil Structures Using Tensor Analysis. - Nguyen Lu Dang Khoa; Bang Zhang; Yang Wang 002; Wei Liu 007; Fang Chen 001; Samir Mustapha; Peter Runcie (PAKDD (1), 2015)

A scalable approach to spectral clustering with SDD solvers. - Nguyen Lu Dang Khoa; Sanjay Chawla (J. Intell. Inf. Syst., 2015)

On Structural Health Monitoring Using Tensor Analysis and Support Vector Machine with Artificial Negative Data. - Prasad Cheema; Nguyen Lu Dang Khoa; Mehrisadat Makki Alamdari; Wei Liu 007; Yang Wang 002; Fang Chen 001; Peter Runcie (CIKM, 2016)

Incremental Commute Time Using Random Walks and Online Anomaly Detection. - Nguyen Lu Dang Khoa; Sanjay Chawla (ECML/PKDD (1), 2016)

Smart Infrastructure Maintenance Using Incremental Tensor Analysis: Extended Abstract. - Nguyen Lu Dang Khoa; Ali Anaissi; Yang Wang 002 (CIKM, 2017)

Self-advised Incremental One-Class Support Vector Machines: An Application in Structural Health Monitoring. - Ali Anaissi; Nguyen Lu Dang Khoa; Thierry Rakotoarivelo; Mehri Makki Alamdari; Yang Wang 002 (ICONIP (1), 2017)

Adaptive One-Class Support Vector Machine for Damage Detection in Structural Health Monitoring. - Ali Anaissi; Nguyen Lu Dang Khoa; Samir Mustapha; Mehrisadat Makki Alamdari; Ali Braytee; Yang Wang 002; Fang Chen 001 (PAKDD (1), 2017)

Deep Autoencoder for Recommender Systems: Parameter Influence Analysis. - Dai Hoang Tran; Zawar Hussain; Wei Zhang 098; Khoa L. D. Nguyen; Nguyen Hoang Tran; Quan Z. Sheng (ACIS, 2018)

A Tensor-based Structural Health Monitoring Approach for Aeroservoelastic Systems. - Prasad Cheema; Nguyen Lu Dang Khoa; Moray Kidd; Gareth A. Vio (CoRR, 2018)

Automated parameter tuning in one-class support vector machine: an application for damage detection. - Ali Anaissi; Nguyen Lu Dang Khoa; Yang Wang 002 (Int. J. Data Sci. Anal., 2018)

A Tensor-Based Structural Damage Identification and Severity Assessment. - Ali Anaissi; Mehrisadat Makki Alamdari; Thierry Rakotoarivelo; Nguyen Lu Dang Khoa (Sensors, 2018)

Adaptive Online One-Class Support Vector Machines with Applications in Structural Health Monitoring. - Ali Anaissi; Nguyen Lu Dang Khoa; Thierry Rakotoarivelo; Mehrisadat Makki Alamdari; Yang Wang 002 (ACM Trans. Intell. Syst. Technol., 2018)

Structural Health Monitoring Using Machine Learning Techniques and Domain Knowledge Based Features. - Nguyen Lu Dang Khoa; Mehrisadat Makki Alamdari; Thierry Rakotoarivelo; Ali Anaissi; Yang Wang 002 (Human and Machine Learning, 2018)

Concept Drift Adaption for Online Anomaly Detection in Structural Health Monitoring. - Hongda Tian; Nguyen Lu Dang Khoa; Ali Anaissi; Yang Wang 002; Fang Chen 001 (CIKM, 2019)

Online Data Fusion Using Incremental Tensor Learning. - Nguyen Lu Dang Khoa; Hongda Tian; Yang Wang 002; Fang Chen 001 (PAKDD (1), 2019)

Incremental commute time and its online applications. - Nguyen Lu Dang Khoa; Yang Wang 002; Sanjay Chawla (Pattern Recognit., 2019)

HeteGraph: A Convolutional Framework for Graph Learning in Recommender Systems. - Dai Hoang Tran; Abdulwahab Aljubairy; Munazza Zaib; Quan Z. Sheng; Wei Emma Zhang; Nguyen Hoang Tran; Khoa L. D. Nguyen (IJCNN, 2020)

Robust Deep Learning Methods for Anomaly Detection. - Raghavendra Chalapathy; Nguyen Lu Dang Khoa; Sanjay Chawla (KDD, 2020)

Long-Term Water Pipe Condition Assessment: A Semiparametric Model Using Gaussian Process and Survival Analysis. - Dilusha Weeraddana; Harini Hapuarachchi; Lakshitha Kumarapperuma; Nguyen Lu Dang Khoa; Chen Cai (PAKDD (2), 2020)

Energy Consumption Forecasting Using a Stacked Nonparametric Bayesian Approach. - Dilusha Weeraddana; Nguyen Lu Dang Khoa; Lachlan O'Neil; Weihong Wang; Chen Cai (ECML/PKDD (5), 2020)

Deep Conversational Recommender Systems: A New Frontier for Goal-Oriented Dialogue Systems. - Dai Hoang Tran; Quan Z. Sheng; Wei Emma Zhang; Salma Abdalla Hamad; Munazza Zaib; Nguyen Hoang Tran; Lina Yao 001; Nguyen Lu Dang Khoa (CoRR, 2020)

Dual-Stage Bayesian Sequence to Sequence Embeddings for Energy Demand Forecasting. - Frances Cameron-Muller; Dilusha Weeraddana; Raghav Chalapathy; Nguyen Lu Dang Khoa (PAKDD (1), 2021)

Deep News Recommendation with Contextual User Profiling and Multifaceted Article Representation. - Dai Hoang Tran; Salma Abdalla Hamad; Munazza Zaib; Abdulwahab Aljubairy; Quan Z. Sheng; Wei Emma Zhang; Nguyen Hoang Tran; Nguyen Lu Dang Khoa (WISE (2), 2021)

The Application Of Machine Learning To Paint Condition Assessment Using Hyperspectral Data. - Ayoub Alayoub; Samer Abed El Rahim; Samir Mustapha; Darine Salam; Ali Tehrani; Nguyen Lu Dang Khoa (WHISPERS, 2022)

Deep Conversational Recommender Systems: Challenges and Opportunities. - Dai Hoang Tran; Quan Z. Sheng; Wei Emma Zhang; Salma Abdalla Hamad; Nguyen Lu Dang Khoa; Nguyen Hoang Tran (Computer, 2022)

Let Trajectories Speak Out the Traffic Bottlenecks. - Hui Luo 001; Zhifeng Bao; Gao Cong; J. Shane Culpepper; Nguyen Lu Dang Khoa (ACM Trans. Intell. Syst. Technol., 2022)

CupMar: A deep learning model for personalized news recommendation based on contextual user-profile and multi-aspect article representation. - Dai Hoang Tran; Quan Z. Sheng; Wei Emma Zhang; Nguyen Hoang Tran; Nguyen Lu Dang Khoa (World Wide Web (WWW), 2023)

HeteGraph: graph learning in recommender systems via graph convolutional networks. - Dai Hoang Tran; Quan Z. Sheng; Wei Emma Zhang; Abdulwahab Aljubairy; Munazza Zaib; Salma Abdalla Hamad; Nguyen Hoang Tran; Nguyen Lu Dang Khoa (Neural Comput. Appl., 2023)