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Approximation vector machines for large-scale online learning

T. Le, T. Nguyen, V. Nguyen, D. Phung

2017 / Vol. 18, pp. 3962 - 4016 / The Journal of Machine Learning Research

Towards Scalable Bayesian Nonparametric Methods for Data Analytics

H. Viet

2017 / Doctor of Philosophy (Information Technology), School of Information Technology

Machine Learning in Healthcare: An Investigation into Model Stability

S. Gopakumar

2017 / Doctor of Philosophy (Information Technology), School of Information Technology

Energy-Based Localized Anomaly Detection in Video Surveillance

H. Vu, T. Nguyen, A. Travers, S. Venkatesh, D. Phung

2017 / pp. 641 - 653 / Pacific-Asia Conference on Knowledge Discovery and Data Mining

Deep learning to attend to risk in ICU

P. Nguyen, T. Tran, S. Venkatesh

2017 / pp. 25 - 29 / KDH 2017: Proceedings of the 2nd International Workshop on Knowledge Discovery in Healthcare Data 2017

Predicting the delay of issues with due dates in software projects

M. Choetkiertikul, H. Dam, T. Tran, A. Ghose

2017 / Vol. 22, pp. 1223 - 1263 / Empirical Software Engineering

Graph Classification via Deep Learning with Virtual Nodes

T. Pham, T. Tran, H. Dam, S. Venkatesh

2017 / Third Representation Learning for Graphs Workshop (ReLiG 2017)

Learning Recurrent Matrix Representation

K. Do, T. Tran, S. Venkatesh

2017 / Third Representation Learning for Graphs Workshop (ReLiG 2017)

Preference Relation-based Markov Random Fields for Recommender Systems

S. Liu, G. Li, T. Tran, J. Yuan

2017 / Vol. 246, pp. 523 - 546 / Machine Learning

Finding Algebraic Structure of Care in Time: A Deep Learning Approach

P. Nguyen, T. Tran, S. Venkatesh

2017 / NIPS Workshop on Machine Learning for Health (ML4H)

A Generic Neural Architecture for Multiple Inputs and Outputs

T. Pham, T. Tran, S. Venkatesh

2017 / NIPS Workshop on Women in Machine Learning (WiML 2017)

High Dimensional Bayesian Optimization Using Dropout

C. Li, S. Gupta, S. Rana, V. Nguyen, S. Venkatesh, A. Shilton

2017 / pp. 2096 - 2102 / International Joint Conference on Artificial Intelligence

Effective sparse imputation of patient conditions in electronic medical records for emergency risk predictions

B. Saha, S. Gupta, D. Phung, S. Venkatesh

2017 / Vol. 53, pp. 1 - 28 / Knowledge and Information Systems

Analysing the History of Autism Spectrum Disorder using Topic Models

A. Beykikhoshk, O. Arandjelovic, S. Venkatesh, D. Phung

2016 / pp. 762 - 771 / Proceedings of the 3rd International Conference on Data Science and Advanced Analytics (DSAA '16)

Scalable Nonparametric Bayesian Multilevel Clustering

V. Huynh, D. Q. Phung, S. Venkatesh, X. Nguyen, M. D. Hoffman, H. Bui

2016 / pp. 289 - 298 / The 32th Conference on Uncertainty in Artificial Intelligence