Truyen Tran

portrait

Truyen Tran (PhD)

Lecturer
PraDa, School of Information Technology
Deakin University
Locked Bag 20000
Geelong VIC 3220

truyen.tran {_at_} deakin.edu.au Research fellow
IMPCA, Department of Computing
Curtin University of Technology
Kent St, Bentley, WA 6102, Australia

Current research projects

Health analytics
Model stability
Representation learning
Recommender systems
News/Media
(12/2014) PhD students wanted for 2015 intake.
(12/2014) I won a 2014 CRESP Best Research Paper Award (Early Career, shared with Dr Bregje van Spijke from ANU).
(10/2014) Machines learn to pick up the cues (Deakin press release).
(4/2014) I'm now a Kaggle Master.
(12/2013) Svetha won Smart Geelong Researcher of the Year Awards 2013.

Publications

Working/Under review

Learning vector representation of medical objects via EMR-driven nonnegative restricted Boltzmann machines (eNRBM), Truyen Tran, Tu Dinh Nguyen, Dinh Phung and Svetha Venkatesh, Journal of Biomedical Informatics (Major revision).

A Framework for Feature Extraction from Hospital Medical Data with Applications in Risk Prediction, Truyen Tran, Wei Luo, Dinh Phung, Sunil Gupta, Santu Rana, Richard Lee Kennedy, Ann Larkins and Svetha Venkatesh, BMC Informatics (Minor revision).

Modelling Human Preferences for Ranking and Collaborative Filtering: A Probabilistic Ordered Partition Approach, Truyen Tran, Dinh Phung and Svetha Venkatesh, KAIS (Major revision).

Screening for Preterm Birth Risk with A Routine Perinatal Data collection, Wei Luo, Emily Y-S Huning, Truyen Tran, Dinh Phung and Svetha Venkatesh.

Learning patient representation and similarities, Tu D. Nguyen, Truyen Tran, D. Phung, and S. Venkatesh.

Graph-induced restricted Boltzmann machines for document modeling, Tu D. Nguyen, Truyen Tran, D. Phung, and S. Venkatesh, Submitted to Information Sciences.

Collaborative filtering via network-driven restricted Boltzmann machines, Truyen Tran, Dinh Phung, and Svetha Venkatesh.

2015

Tensor-variate Restricted Boltzmann Machines, Tu D. Nguyen, Truyen Tran, D. Phung, and S. Venkatesh, AAAI 2015.

2014

Tree-based Iterated Local Search for Markov Random Fields with Applications in Image Analysis, Truyen Tran, Dinh Phung and Svetha Venkatesh, Journal of Heuristics, 2014, DOI:10.1007/s10732-014-9270-1

Stabilizing high-dimensional prediction models using feature graphs, Shivapratap Gopakumar, Truyen Tran, Tu Dinh Nguyen, Dinh Phung, and Svetha Venkatesh, IEEE Journal of Biomedical and Health Informatics, 2014 DOI:10.1109/JBHI.2014.2353031S

Ordinal random fields for recommender systems, Shaowu Liu, Truyen Tran, Gang Li, Yuan Jiang, ACML'14, Nha Trang, Vietnam, Nov 2014.

Stabilizing sparse Cox model using clinical structures in electronic medical records, S Gopakumar, Truyen Tran, D Phung, S Venkatesh, 2nd International Workshop on Pattern Recognition for Healthcare Analytics, August 2014

Speed up health research through topic modeling of coded clinical data, Wei Luo, Dinh Phung, Vu Nguyen, Truyen Tran, Svetha Venkatesh, 2nd International Workshop on Pattern Recognition for Healthcare Analytics, August 2014

iPoll: Automatic polling using online search, Thin Nguyen, Dinh Phung, Wei Luo, Truyen Tran, Svetha Venkatesh, Proc. of 15th International Conference on Web Information System Engineering (WISE), 2014

HealthMap: A visual platform for patient suicide risk review, Santu Rana, Wei Luo, Truyen Tran, Dinh Phung, Svetha Venkatesh and Richard Harvey, HISA Big Data, Melbourne April, 2014

Predicting unplanned readmission after myocardial infarction from routinely collected administrative hospital data, Santu Rana, Truyen Tran, Wei Luo, Dinh Phung, Richard L. Kennedy and Svetha Venkatesh, Australian Health Review, 2014 doi:dx.doi.org/10.1071/AH14059

Risk stratification using data from electronic medical records better predict suicide risks than clinician assessments, Truyen Tran, Wei Luo, Dinh Phung, Richard Harvey, Michael Berk, Richard Lee Kennedy, Svetha Venkatesh, BMC Psychiatry, 14:76, 2014.

Machine-learning prediction of cancer survival: a retrospective study using electronic administrative records and a cancer registry, Sunil Gupta, Truyen Tran, Wei Luo, Dinh Phung, Richard Lee Kennedy, Adam Broad, David Campbell, David Kipp, Madhu Singh, Mustafa Khasraw, Leigh Matheson, David M Ashley, Svetha Venkatesh, BMJ Open, 2014, doi:10.1136/bmjopen-2013-004007

Stabilized sparse ordinal regression for medical risk stratification, Truyen Tran, Dinh Phung, Wei Luo, and Svetha Venkatesh, Knowledge and Information Systems, 2014, DOI: 10.1007/s10115-014-0740-4.

2013

An integrated framework for suicide risk prediction, Truyen Tran, Dinh Phung, Wei Luo, Richard Harvey, Michael Berk, and Svetha Venkatesh, In Proc. of 19th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), Chicago, USA, August, 2013.

Thurstonian Boltzmann machines: Learning from multiple inequalities, Truyen Tran, D. Phung, and S. Venkatesh, In Proc. of 30th International Conference in Machine Learning (ICML’13), Atlanta, USA, June, 2013.

Learning parts-based representations with Nonnegative Restricted Boltzmann Machine, Tu D. Nguyen, Truyen Tran, D. Phung, and S. Venkatesh, Journal of Machine Learning Research (JMLR) Workshop and Conference Proceedings, Vol. 29, Proc. of 5th Asian Conference on Machine Learning, Nov 2013.

Latent patient profile modelling and applications with Mixed-Variate Restricted Boltzmann Machine, Tu D. Nguyen, Truyen Tran, D. Phung, and S. Venkatesh, In Proc. of 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD’13), Gold Coast, Australia, April 2013.

Learning sparse latent representation and distance metric for image retrieval, Tu D. Nguyen, Truyen Tran, D. Phung, and S. Venkatesh, In Proc. of IEEE International Conference on Multimedia and Expo (ICME), San Jose, California, USA, July 2013.

2012

Learning from Ordered Sets and Applications in Collaborative Ranking, Truyen Tran, Dinh Phung and Svetha Venkatesh, in Proc. of. the 4th Asian Conference on Machine Learning (ACML2012), Singapore, Nov 2012.

Cumulative Restricted Boltzmann Machines for Ordinal Matrix Data Analysis, Truyen Tran, Dinh Phung and Svetha Venkatesh, in Proc. of. the 4th Asian Conference on Machine Learning (ACML2012), Singapore, Nov 2012.

Embedded Restricted Boltzmann Machines for Fusion of Mixed Data Types and Applications in Social Measurements Analysis, Truyen Tran, Dinh Phung, Svetha Venkatesh, To appear in Proc. of 15-th International Conference on Information Fusion (FUSION-12), Singapore, July 2012.

A Sequential Decision Approach to Ordinal Preferences in Recommender Systems, Truyen Tran, Dinh Phung, Svetha Venkatesh, To appear in Proc. of 25-th Conference on Artificial Intelligence (AAAI-12), Toronto, Canada, July 2012.

Learning Boltzmann Distance Metric for Face Recognition, Truyen Tran, Dinh Phung, Svetha Venkatesh, To appear in Proc. of IEEE International Conference on Multimedia & Expo (ICME-12), Melbourne, Australia, July 2012.

2011

Mixed-Variate Restricted Boltzmann Machines, Truyen Tran, Dinh Phung and Svetha Venkatesh, in Proc. of. the 3rd Asian Conference on Machine Learning (ACML2011), Taoyuan, Taiwan, Nov 2011.

Probabilistic Models over Ordered Partitions with Applications in Document Ranking and Collaborative Filtering
T. Truyen, D. Phung, and S. Venkatesh, in Proc. of SIAM Int. Conf. on Data Mining (SDM11), April, Arizona, USA, 2011

2010

Nonnegative Shared Subspace Learning and Its Application to Social Media Retrieval, S. Gupta, D. Phung, B. Adams, Tran The Truyen and Svetha Venkatesh, In Proc. of 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 25-28 Jul, Washington DC, 2010

Classification and Pattern Discovery of Mood in Weblogs, Thin Nguyen, Dinh Q. Phung, Brett Adams, Truyen Tran and Svetha Venkatesh. In Proc. of Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 21-24 June, Hyderabad, India, 2010.

2009

MCMC for Hierarchical Semi-Markov Conditional Random Fields, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh and Hung H. Bui. In NIPS'09 Workshop on Deep Learning for Speech Recognition and Related Applications. December, 2009, Whistler, BC, Canada.

Ordinal Boltzmann Machines for Collaborative Filtering. Truyen Tran, Dinh Q. Phung and Svetha Venkatesh. In Proc. of 25th Conference on Uncertainty in Artificial Intelligence, June, 2009, Montreal, Canada. Runner-up for the best paper award.

2004-2008

Hierarchical Semi-Markov Conditional Random Fields for Recursive Sequential Data, Truyen Tran, Dinh Q. Phung, Hung H. Bui, and Svetha Venkatesh. In Proc. of 21st Annual Conference on Neural Information Processing Systems, Dec 2008, Vancouver, Canada. [See technical report and thesis for more details and extensions.]

Constrained Sequence Classification for Lexical Disambiguation, Truyen Tran, Dinh Q. Phung and Svetha Venkatesh. In Proc. of 10th Pacific Rim International Conference on Artificial Intelligence (PRICAI-08), 15-19 Dec 2008, Hanoi, Vietnam.

Learning Discriminative Sequence Models from Partially Labelled Data for Activity Recognition, Truyen Tran, Hung Hai Bui, Dinh Q. Phung and Svetha Venkatesh. In Proc. of 10th Pacific Rim International Conference on Artificial Intelligence (PRICAI-08), 15-19 Dec 2008, Hanoi, Vietnam.

Preference Networks: probabilistic models for recommendation systems, Truyen Tran, Dinh Q. Phung and Svetha Venkatesh, In Proc. of 6th Australasian Data Mining Conference: AusDM 2007, 3-4 Dec, Gold Coast, Australia.

AdaBoost.MRF: Boosted Markov random forests and application to multilevel activity recognition, Truyen Tran, Dinh Quoc Phung, Hung Hai Bui, and Svetha Venkatesh. In Proc. of IEEE Conference on Computer Vision and Pattern Recognition, volume Volume 2, pages 1686-1693, New York, USA, June 2006.

Boosted Markov networks for activity recognition, Truyen Tran, Hung Hai Bui and Svetha Venkatesh, In Proc. of International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP2005), 5-8 Dec, Melbourne, Australia.

Global optimization using Levy flight, Truyen Tran, Trung Thanh Nguyen, Hoang Linh Nguyen, Second National Symposium on Research, Development and Application of Information and Communication Technology (ICT. rda), Vietnam, 2004

Tutorials and Notes

Discrete Combinatorial Optimisation in MAP Estimation

PhD thesis

On Conditional Random Fields: Applications, Feature Selection, Parameter Estimation and Hierarchical Modelling, Depart. Computing, Curtin Uni, Feb, 2008 [Abstract].

Patents

Extracting medical features for risk prediction, Truyen Tran, Santu Rana, Quoc-Dinh Phung, Wei Luo, and Svetha Venkatesh, Provisional patent, June 2013.