Multi-modal abnormality detection in video with unknown data segmentation. - Tien-Vu Nguyen; Dinh Q. Phung; Santu Rana; Duc-Son Pham 001; Svetha Venkatesh (ICPR, 2012)

Higher Order Conditional Random Field for Multi-Label Interactive Image Segmentation. - Tien-Vu Nguyen; Nghia Pham; Trung Tran; Bac Le (RIVF, 2012)

Topic Model Kernel: An Empirical Study towards Probabilistically Reduced Features for Classification. - Tien-Vu Nguyen; Dinh Q. Phung; Svetha Venkatesh (ICONIP (2), 2013)

Interactive browsing system for anomaly video surveillance. - Tien-Vu Nguyen; Dinh Q. Phung; Sunil Gupta 001; Svetha Venkatesh (ISSNIP, 2013)

Bayesian Nonparametric Multilevel Clustering with Group-Level Contexts. - Tien-Vu Nguyen; Dinh Quoc Phung; XuanLong Nguyen; Svetha Venkatesh; Hung Bui 001 (ICML, 2014)

A Bayesian Nonparametric Approach to Multilevel Regression. - Vu Nguyen 001; Dinh Q. Phung; Svetha Venkatesh; Hung Hai Bui (PAKDD (1), 2015)

A Bayesian Nonparametric Approach for Multi-label Classification. - Vu Nguyen 001; Sunil Gupta 001; Santu Rana; Cheng Li 003; Svetha Venkatesh (ACML, 2016)

Multiple Kernel Learning with Data Augmentation. - Khanh Nguyen; Trung Le 001; Vu Nguyen 001; Tu Dinh Nguyen; Dinh Q. Phung (ACML, 2016)

Nonparametric Budgeted Stochastic Gradient Descent. - Trung Le 001; Vu Nguyen 001; Tu Dinh Nguyen; Dinh Q. Phung (AISTATS, 2016)

Cascade Bayesian Optimization. - Thanh Dai Nguyen; Sunil Gupta 001; Santu Rana; Vu Nguyen 001; Svetha Venkatesh; Kyle J. Deane; Paul G. Sanders (Australasian Conference on Artificial Intelligence, 2016)

Learning Multifaceted Latent Activities from Heterogeneous Mobile Data. - Nguyen Thanh Binh 001; Vu Nguyen 001; Nguyen Cong Thuong; Svetha Venkatesh; Mohan Kumar; Dinh Q. Phung (DSAA, 2016)

One-Pass Logistic Regression for Label-Drift and Large-Scale Classification on Distributed Systems. - Vu Nguyen 001; Tu Dinh Nguyen; Trung Le 001; Svetha Venkatesh; Dinh Q. Phung (ICDM, 2016)

Budgeted Batch Bayesian Optimization. - Vu Nguyen 001; Santu Rana; Sunil Kumar Gupta 001; Cheng Li 003; Svetha Venkatesh (ICDM, 2016)

Multiple adverse effects prediction in longitudinal cancer treatment. - Cheng Li 003; Sunil Gupta 001; Santu Rana; Vu Nguyen 001; Svetha Venkatesh; David Ashely; Trish Livingston (ICPR, 2016)

Distributed data augmented support vector machine on Spark. - Tu Dinh Nguyen; Vu Nguyen 001; Trung Le 001; Dinh Q. Phung (ICPR, 2016)

MCNC: Multi-Channel Nonparametric Clustering from heterogeneous data. - Nguyen Thanh Binh 001; Vu Nguyen 001; Svetha Venkatesh; Dinh Q. Phung (ICPR, 2016)

Dual Space Gradient Descent for Online Learning. - Trung Le 001; Tu Dinh Nguyen; Vu Nguyen 001; Dinh Q. Phung (NIPS, 2016)

Sparse Adaptive Multi-hyperplane Machine. - Khanh Nguyen; Trung Le 001; Vu Nguyen 001; Dinh Q. Phung (PAKDD (1), 2016)

Learning Multi-faceted Activities from Heterogeneous Data with the Product Space Hierarchical Dirichlet Processes. - Nguyen Thanh Binh 001; Vu Nguyen 001; Svetha Venkatesh; Dinh Q. Phung (PAKDD Workshops, 2016)

SECC: Simultaneous extraction of context and community from pervasive signals. - Nguyen Cong Thuong; Vu Nguyen 001; Flora D. Salim; Dinh Q. Phung (PerCom, 2016)

Budgeted Semi-supervised Support Vector Machine . - Trung Le 001; Phuong Duong; Mi Dinh; Tu Dinh Nguyen; Vu Nguyen 001; Dinh Q. Phung (UAI, 2016)

Scalable Support Vector Machine for Semi-supervised Learning. - Trung Le 001; Khanh Nguyen; Van Nguyen 002; Vu Nguyen 001; Dinh Q. Phung (CoRR, 2016)

Regret for Expected Improvement over the Best-Observed Value and Stopping Condition. - Vu Nguyen 001; Sunil Gupta 001; Santu Rana; Cheng Li 003; Svetha Venkatesh (ACML, 2017)

GoGP: Fast Online Regression with Gaussian Processes. - Trung Le 001; Khanh Nguyen; Vu Nguyen 001; Tu Dinh Nguyen; Dinh Q. Phung (ICDM, 2017)

Bayesian Optimization in Weakly Specified Search Space. - Vu Nguyen 001; Sunil Gupta 001; Santu Rana; Cheng Li 003; Svetha Venkatesh (ICDM, 2017)

High Dimensional Bayesian Optimization with Elastic Gaussian Process. - Santu Rana; Cheng Li 003; Sunil Gupta 001; Vu Nguyen 001; Svetha Venkatesh (ICML, 2017)

High Dimensional Bayesian Optimization using Dropout. - Cheng Li 003; Sunil Gupta 001; Santu Rana; Vu Nguyen 001; Svetha Venkatesh; Alistair Shilton (IJCAI, 2017)

Discriminative Bayesian Nonparametric Clustering. - Vu Nguyen 001; Dinh Q. Phung; Trung Le 001; Hung Bui 001 (IJCAI, 2017)

Budgeted Batch Bayesian Optimization With Unknown Batch Sizes. - Vu Nguyen 001; Santu Rana; Sunil Gupta 001; Cheng Li 003; Svetha Venkatesh (CoRR, 2017)

Approximation Vector Machines for Large-scale Online Learning. - Trung Le 001; Tu Dinh Nguyen; Vu Nguyen 001; Dinh Q. Phung (J. Mach. Learn. Res., 2017)

A Simultaneous Extraction of Context and Community from pervasive signals using nested Dirichlet process. - Nguyen Cong Thuong; Vu Nguyen 001; Flora D. Salim; Duc Viet Le 002; Dinh Q. Phung (Pervasive Mob. Comput., 2017)

Accelerating Experimental Design by Incorporating Experimenter Hunches. - Cheng Li 003; Santu Rana; Sunil Gupta 001; Vu Nguyen 001; Svetha Venkatesh; Alessandra Sutti; David Rubin de Celis Leal; Teo Slezak; Murray Height; Mazher Mohammed; Ian Gibson (ICDM, 2018)

Label-Sensitive Task Grouping by Bayesian Nonparametric Approach for Multi-Task Multi-Label Learning. - Xiao Zhang 015; Wenzhong Li; Vu Nguyen 001; Fuzhen Zhuang; Hui Xiong 001; Sanglu Lu (IJCAI, 2018)

Algorithmic Assurance: An Active Approach to Algorithmic Testing using Bayesian Optimisation. - Shivapratap Gopakumar; Sunil Gupta 001; Santu Rana; Vu Nguyen 001; Svetha Venkatesh (NeurIPS, 2018)

Exploration Enhanced Expected Improvement for Bayesian Optimization. - Julian Berk; Vu Nguyen 001; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (ECML/PKDD (2), 2018)

Practical Batch Bayesian Optimization for Less Expensive Functions. - Vu Nguyen 001; Sunil Gupta 001; Santu Rana; Cheng Li 003; Svetha Venkatesh (CoRR, 2018)

Bayesian Optimization for Accelerating Hyper-Parameter Tuning. - Vu Nguyen 001 (AIKE, 2019)

Efficient Bayesian Optimization for Uncertainty Reduction Over Perceived Optima Locations. - Vu Nguyen 001; Sunil Gupta 001; Santu Rana; My T. Thai; Cheng Li 003; Svetha Venkatesh (ICDM, 2019)

GoGP: scalable geometric-based Gaussian process for online regression. - Trung Le 001; Khanh Nguyen; Vu Nguyen 001; Tu Dinh Nguyen; Dinh Q. Phung (Knowl. Inf. Syst., 2019)

Filtering Bayesian optimization approach in weakly specified search space. - Vu Nguyen 001; Sunil Gupta 001; Santu Rana; Cheng Li 003; Svetha Venkatesh (Knowl. Inf. Syst., 2019)

Incorporating Expert Prior Knowledge into Experimental Design via Posterior Sampling. - Cheng Li 003; Sunil Gupta 001; Santu Rana; Vu Nguyen 001; Antonio Robles-Kelly; Svetha Venkatesh (CoRR, 2020)

Bayesian optimisation in unknown bounded search domains. - Julian Berk; Sunil Gupta 001; Santu Rana; Vu Nguyen 001; Svetha Venkatesh (Knowl. Based Syst., 2020)

Personalized brain stimulation for effective neurointervention across participants. - Nienke E. R. van Bueren; Thomas L. Reed; Vu Nguyen 001; James G. Sheffield; Sanne H. G. van der Ven; Michael A. Osborne; Evelyn H. Kroesbergen; Roi Cohen Kadosh (PLoS Comput. Biol., 2021)

Self-Supervision Improves Diffusion Models for Tabular Data Imputation. - Yixin Liu 001; Thalaiyasingam Ajanthan; Hisham Husain; Vu Nguyen 001 (CIKM, 2024)

High Dimensional Bayesian Optimization using Lasso Variable Selection. - Vu Viet Hoang; Hung The Tran; Sunil Gupta 001; Vu Nguyen 001 (AISTATS, 2025)

Personalized home based neurostimulation via AI optimization augments sustained attention. - Roi Cohen Kadosh; Delia Ciobotaru; Malin I. Karstens; Vu Nguyen 001 (npj Digit. Medicine, 2025)