Major Projects
ARC DP180101192 (with Geoff McLachlan, UQ; and Sharon Lee, UQ): Classification methods for providing personalised and class decisions.
Past Projects
ARC DE170101134: Feasible algorithms for big inference.
Journal Article: Multivariate expectile-based distribution: Properties, Bayesian inference, and applications
Arbel, Julyan, Girard, Stéphane, Nguyen, Hien Duy and Usseglio-Carleve, Antoine (2023). Multivariate expectile-based distribution: Properties, Bayesian inference, and applications. Journal of Statistical Planning and Inference, 225, 146-170. doi: 10.1016/j.jspi.2022.12.001
Journal Article: Finite sample inference for empirical Bayesian methods
Nguyen, Hien Duy and Gupta, Mayetri (2023). Finite sample inference for empirical Bayesian methods. Scandinavian Journal of Statistics. doi: 10.1111/sjos.12643
Journal Article: Passive superconducting circulator on a chip
Navarathna, Rohit, Le, Dat Thanh, Rosario Hamann, Andrés, Nguyen, Hien Duy, Stace, Thomas M. and Fedorov, Arkady (2023). Passive superconducting circulator on a chip. Physical Review Letters, 130 (3) 037001. doi: 10.1103/physrevlett.130.037001
Stochastic majorization--minimization algorithms for data science
(2023–2026) ARC Discovery Projects
Feasible algorithms for big inference
(2021) ARC Discovery Early Career Researcher Award
Classification methods for providing personalised and class decisions
(2018–2022) ARC Discovery Projects
Deep learning approaches to the modelling of neuroimaging and neuroactivation data
Doctor Philosophy
Big data-appropriate clustering via stochastic approximation and Gaussian mixture models
Nguyen, Hien D. and Jones, Andrew Thomas (2019). Big data-appropriate clustering via stochastic approximation and Gaussian mixture models. Data analytics: concepts, techniques, and applications. (pp. 55-72) edited by Mohiuddin Ahmed and Al-Sakib Khan Pathan. Boca Raton, FL, United States: CRC Press. doi: 10.1201/9780429446177-3
Nguyen, Hien D., McLachlan, Geoffrey J. and Hill, Michelle M. (2017). Statistical evaluation of labeled comparative profiling proteomics experiments using permutation test. Proteome bioinformatics. (pp. 109-117) edited by Shivakumar Keerthikumar and Suresh Mathivanan. New York, NY United States: Humana Press. doi: 10.1007/978-1-4939-6740-7_9
Multivariate expectile-based distribution: Properties, Bayesian inference, and applications
Arbel, Julyan, Girard, Stéphane, Nguyen, Hien Duy and Usseglio-Carleve, Antoine (2023). Multivariate expectile-based distribution: Properties, Bayesian inference, and applications. Journal of Statistical Planning and Inference, 225, 146-170. doi: 10.1016/j.jspi.2022.12.001
Finite sample inference for empirical Bayesian methods
Nguyen, Hien Duy and Gupta, Mayetri (2023). Finite sample inference for empirical Bayesian methods. Scandinavian Journal of Statistics. doi: 10.1111/sjos.12643
Passive superconducting circulator on a chip
Navarathna, Rohit, Le, Dat Thanh, Rosario Hamann, Andrés, Nguyen, Hien Duy, Stace, Thomas M. and Fedorov, Arkady (2023). Passive superconducting circulator on a chip. Physical Review Letters, 130 (3) 037001. doi: 10.1103/physrevlett.130.037001
Functional connectivity subtypes associate robustly with ASD diagnosis
Urchs, Sebastian G.W., Tam, Angela, Orban, Pierre, Moreau, Clara, Benhajali, Yassine, Nguyen, Hien Duy, Evans, Alan C. and Bellec, Pierre (2022). Functional connectivity subtypes associate robustly with ASD diagnosis. eLife, 11 e56257, 1-34. doi: 10.7554/elife.56257
Order selection with confidence for finite mixture models
Nguyen, Hien D., Fryer, Daniel and McLachlan, Geoffrey J. (2022). Order selection with confidence for finite mixture models. Journal of the Korean Statistical Society, 52 (1), 154-184. doi: 10.1007/s42952-022-00195-z
Refining the estimation of amphetamine consumption by wastewater-based epidemiology
Gao, Jianfa, Burgard, Daniel A., Tscharke, Benjamin J., Lai, Foon Yin, O'Brien, Jake W., Nguyen, Hien D., Zheng, Qiuda, Li, Jiaying, Du, Peng, Li, Xiqing, Wang, Degao, Castiglioni, Sara, Cruz-Cruz, Copytzy, Baz-Lomba, Jose Antonio, Yargeau, Viviane, Emke, Erik, Thomas, Kevin V., Mueller, Jochen F. and Thai, Phong K. (2022). Refining the estimation of amphetamine consumption by wastewater-based epidemiology. Water Research, 225 119182, 1-8. doi: 10.1016/j.watres.2022.119182
Forbes, Florence, Nguyen, Hien Duy, Nguyen, TrungTin and Arbel, Julyan (2022). Summary statistics and discrepancy measures for approximate Bayesian computation via surrogate posteriors. Statistics and Computing, 32 (5) 85. doi: 10.1007/s11222-022-10155-6
Quantification of behavioural variation among sheep grazing on pasture using accelerometer sensors
Almasi, F., Nguyen, H., Heydarian, D., Sohi, R., Nikbin, S., Jenvey, C. J., Halliwell, E., Ponnampalam, E. N., Desai, A., Jois, M. and Stear, M. J. (2022). Quantification of behavioural variation among sheep grazing on pasture using accelerometer sensors. Animal Production Science, 62 (15), 1527-1538. doi: 10.1071/AN21464
Sohi, Rajneet, Almasi, Fazel, Nguyen, Hien, Carroll, Alexandra, Trompf, Jason, Weerasinghe, Maneka, Bervan, Aidin, Godoy, Boris I., Ahmed, Awais, Stear, Michael J., Desai, Aniruddha and Jois, Markandeya (2022). Determination of ewe behaviour around lambing time and prediction of parturition 7 days prior to lambing by tri-axial accelerometer sensors in an extensive farming system. Animal Production Science, 62 (17), 1729-1738. doi: 10.1071/AN21460
A Festschrift for Geoff McLachlan
Nguyen, Hien, Lee, Sharon and Forbes, Florence (2022). A Festschrift for Geoff McLachlan. Australian and New Zealand Journal of Statistics, 64 (2), 111-116. doi: 10.1111/anzs.12372
Durand, J. B., Forbes, F., Phan, C. D., Truong, L., Nguyen, H. D. and Dama, F. (2022). Bayesian non-parametric spatial prior for traffic crash risk mapping: a case study of Victoria, Australia. Australian and New Zealand Journal of Statistics, 64 (2), 171-204. doi: 10.1111/anzs.12369
Approximation of probability density functions via location-scale finite mixtures in Lebesgue spaces
Nguyen, TrungTin, Chamroukhi, Faicel, Nguyen, Hien D. and McLachlan, Geoffrey J. (2022). Approximation of probability density functions via location-scale finite mixtures in Lebesgue spaces. Communications in Statistics - Theory and Methods, 52 (14), 1-12. doi: 10.1080/03610926.2021.2002360
Modelling the relationships between train commuters’ access modes and traffic safety
Phan, Duc C., Truong, Long T., Nguyen, Hien D. and Tay, Richard (2022). Modelling the relationships between train commuters’ access modes and traffic safety. Journal of Advanced Transportation, 2022 3473397, 1-17. doi: 10.1155/2022/3473397
Global implicit function theorems and the online expectation–maximisation algorithm
Nguyen, Hien Duy and Forbes, Florence (2022). Global implicit function theorems and the online expectation–maximisation algorithm. Australian and New Zealand Journal of Statistics, 64 (2), 255-281. doi: 10.1111/anzs.12356
Nguyen, Trungtin, Nguyen, Hien Duy, Chamroukhi, Faicel and Forbes, Florence (2022). A non-asymptotic approach for model selection via penalization in high-dimensional mixture of experts models. Electronic Journal of Statistics, 16 (2), 4742-4822. doi: 10.1214/22-EJS2057
Nguyen, Hien Duy, Nguyen, TrungTin, Chamroukhi, Faicel and McLachlan, Geoffrey John (2021). Approximations of conditional probability density functions in Lebesgue spaces via mixture of experts models. Journal of Statistical Distributions and Applications, 8 (1) 13. doi: 10.1186/s40488-021-00125-0
Shapley values for feature selection: The good, the bad, and the axioms
Fryer, Daniel, Strumke, Inga and Nguyen, Hien (2021). Shapley values for feature selection: The good, the bad, and the axioms. IEEE Access, 9, 144352-144360. doi: 10.1109/ACCESS.2021.3119110
Model independent feature attributions: Shapley values that uncover non-linear dependencies
Fryer, Daniel Vidali, Strumke, Inga and Nguyen, Hien (2021). Model independent feature attributions: Shapley values that uncover non-linear dependencies. PeerJ Computer Science, 7, e582-23. doi: 10.7717/PEERJ-CS.582
Shapley value confidence intervals for attributing variance explained
Fryer, Daniel, Strümke, Inga and Nguyen, Hien (2020). Shapley value confidence intervals for attributing variance explained. Frontiers in Applied Mathematics and Statistics, 6 587199. doi: 10.3389/fams.2020.587199
Bayesian clustering of skewed and multimodal data using geometric skewed normal distributions
Redivo, Edoardo, Nguyen, Hien D. and Gupta, Mayetri (2020). Bayesian clustering of skewed and multimodal data using geometric skewed normal distributions. Computational Statistics and Data Analysis, 152 107040. doi: 10.1016/j.csda.2020.107040
Approximation by finite mixtures of continuous density functions that vanish at infinity
Nguyen, T. Tin, Nguyen, Hien D., Chamroukhi, Faicel and McLachlan, Geoffrey J. (2020). Approximation by finite mixtures of continuous density functions that vanish at infinity. Cogent Mathematics and Statistics, 7 (1). doi: 10.1080/25742558.2020.1750861
The fully visible Boltzmann machine and the Senate of the 45th Australian Parliament in 2016
Bagnall, Jessica J., Jones, Andrew T., Karavarsamis, Natalie and Nguyen, Hien D. (2020). The fully visible Boltzmann machine and the Senate of the 45th Australian Parliament in 2016. Journal of Computational Social Science, 3 (1), 55-81. doi: 10.1007/s42001-019-00055-7
On strict sub-Gaussianity, optimal proxy variance and symmetry for bounded random variables
Arbel, Julyan, Marchal, Olivier and Nguyen, Hien D. (2020). On strict sub-Gaussianity, optimal proxy variance and symmetry for bounded random variables. ESAIM - Probability and Statistics, 24, 39-55. doi: 10.1051/ps/2019018
Mini-batch learning of exponential family finite mixture models
Nguyen, Hien D., Forbes, Florence and McLachlan, Geoffrey J. (2020). Mini-batch learning of exponential family finite mixture models. Statistics and Computing, 30 (4), 731-748. doi: 10.1007/s11222-019-09919-4
Approximate Bayesian computation via the energy statistic
Nguyen, Hien Duy, Arbel, Julyan, Lu, Hongliang and Forbes, Florence (2020). Approximate Bayesian computation via the energy statistic. IEEE Access, 8 9142178, 131683-131698. doi: 10.1109/access.2020.3009878
Vladimirova, Mariia, Girard, Stéphane, Nguyen, Hien and Arbel, Julyan (2020). Sub-Weibull distributions: Generalizing sub-Gaussian and sub-Exponential properties to heavier tailed distributions. Stat, 9 (1) e318. doi: 10.1002/sta4.318
Approximation results regarding the multiple-output Gaussian gated mixture of linear experts model
Nguyen, Hien D., Chamroukhi, Faicel and Forbes, Florence (2019). Approximation results regarding the multiple-output Gaussian gated mixture of linear experts model. Neurocomputing, 366, 208-214. doi: 10.1016/j.neucom.2019.08.014
Truong, Long T., Nguyen, Hang T.T., Nguyen, Hien D. and Vu, Hung V. (2019). Pedestrian overpass use and its relationships with digital and social distractions, and overpass characteristics. Accident Analysis and Prevention, 131, 234-238. doi: 10.1016/j.aap.2019.07.004
studentlife: tidy handling and navigation of a valuable mobile-health dataset
Fryer, Daniel, Nguyen, Hien and Orban, Pierre (2019). studentlife: tidy handling and navigation of a valuable mobile-health dataset. Journal of Open Source Software, 4 (40), 1587. doi: 10.21105/joss.01587
On approximations via convolution-defined mixture models
Nguyen, Hien D. and McLachlan, Geoffrey (2019). On approximations via convolution-defined mixture models. Communications in Statistics - Theory and Methods, 48 (16), 3945-3955. doi: 10.1080/03610926.2018.1487069
Nguyen, Hien D., Yee, Yohan, McLachlan, Geoffrey J. and Lerch, Jason P. (2019). False discovery rate control for grouped or discretely supported p-values with application to a neuroimaging study. SORT, 43 (2), 1-22. doi: 10.2436/20.8080.02.87
Model-based clustering and classification of functional data
Chamroukhi, Faicel and Nguyen, Hien D. (2019). Model-based clustering and classification of functional data. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 9 (4) e1298. doi: 10.1002/widm.1298
BoltzMM: an R package for maximum pseudolikelihood estimation of fully-visible Boltzmann machines
Jones, Andrew T., Bagnall, Jessica J. and Nguyen, Hien D. (2019). BoltzMM: an R package for maximum pseudolikelihood estimation of fully-visible Boltzmann machines. Journal of Open Source Software, 4 (34) 1193, 1193. doi: 10.21105/joss.01193
Nguyen, Hien D. (2019). Asymptotic normality of the time-domain generalized least squares estimator for linear regression models. Stat, 8 (1) e248. doi: 10.1002/sta4.248
Nguyen, Hien (2019). Preface. Communications in Computer and Information Science, 1150 CCIS.
Randomized mixture models for probability density approximation and estimation
Nguyen, Hien D., Wang, Dianhui and McLachlan, Geoffrey J. (2018). Randomized mixture models for probability density approximation and estimation. Information Sciences, 467, 135-148. doi: 10.1016/j.ins.2018.07.056
logKDE: log-transformed kernel density estimation
Jones, Andrew T., Nguyen, Hien D. and McLachlan, Geoffrey J. (2018). logKDE: log-transformed kernel density estimation. Journal of Open Source Software, 3 (28) 870, 870. doi: 10.21105/joss.00870
Practical and theoretical aspects of mixture-of-experts modeling: an overview
Nguyen, Hien D. and Chamroukhi, Faicel (2018). Practical and theoretical aspects of mixture-of-experts modeling: an overview. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 8 (4) e1246. doi: 10.1002/widm.1246
Stream-suitable optimization algorithms for some soft-margin support vector machine variants
Nguyen, Hien D., Jones, Andrew T. and McLachlan, Geoffrey J. (2018). Stream-suitable optimization algorithms for some soft-margin support vector machine variants. Japanese Journal of Statistics and Data Science., 1 (1), 81-108. doi: 10.1007/s42081-018-0001-y
A globally convergent algorithm for a lasso-penalized mixture of linear regression models
Lloyd-Jones, Luke R., Nguyen, Hien D. and McLachlan, Geoffrey J. (2018). A globally convergent algorithm for a lasso-penalized mixture of linear regression models. Computational Statistics and Data Analysis, 119, 19-38. doi: 10.1016/j.csda.2017.09.003
Near universal consistency of the maximum pseudolikelihood estimator for discrete models
Nguyen, Hien D. (2018). Near universal consistency of the maximum pseudolikelihood estimator for discrete models. Journal of the Korean Statistical Society, 47 (1), 90-98. doi: 10.1016/j.jkss.2017.10.001
Chunked-and-averaged estimators for vector parameters
Nguyen, Hien D. and McLachlan, Geoffrey J. (2018). Chunked-and-averaged estimators for vector parameters. Statistics and Probability Letters, 137, 336-342. doi: 10.1016/j.spl.2018.02.051
Orban, Pierre, Dansereau, Christian, Desbois, Laurence, Mongeau-Pérusse, Violaine, Giguère, Charles-Édouard, Nguyen, Hien, Mendrek, Adrianna, Stip, Emmanuel and Bellec, Pierre (2018). Multisite generalizability of schizophrenia diagnosis classification based on functional brain connectivity. Schizophrenia Research, 192, 167-171. doi: 10.1016/j.schres.2017.05.027
Whole-volume clustering of time series data from zebrafish brain calcium images via mixture modeling
Nguyen, Hien D., Ullmann, Jeremy F. P., Mclachlan, Geoffrey J., Voleti, Venkatakaushik, Li, Wenze, Hillman, Elizabeth M. C., Reutens, David C. and Janke, Andrew L. (2017). Whole-volume clustering of time series data from zebrafish brain calcium images via mixture modeling. Statistical Analysis and Data Mining, 11 (1), 5-16. doi: 10.1002/sam.11366
Some theoretical results regarding the polygonal distribution
Nguyen, Hien D. and McLachlan, Geoffrey J. (2017). Some theoretical results regarding the polygonal distribution. Communications in Statistics: Theory and Methods, 47 (20), 5083-5095. doi: 10.1080/03610926.2017.1386312
Oyarzun, Carlos, Sanjurjo, Adam and Nguyuen, Hien (2017). Response functions. European Economic Review, 98, 1-31. doi: 10.1016/j.euroecorev.2017.06.011
Maximum pseudolikelihood estimation for model-based clustering of time series data
Nguyen, Hien D., McLachlan, Geoffrey J., Orban, Pierre, Bellec, Pierre and Janke, Andrew L. (2017). Maximum pseudolikelihood estimation for model-based clustering of time series data. Neural Computation, 29 (4), 990-1020. doi: 10.1162/NECO_a_00938
Nguyen, Hien D. (2017). An introduction to majorization-minimization algorithms for machine learning and statistical estimation. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 7 (2) e1198. doi: 10.1002/widm.1198
A universal approximation theorem for mixture-of-experts models
Nguyen, Hien D., Lloyd-Jones, Luke R. and McLachlan, Geoffrey J. (2016). A universal approximation theorem for mixture-of-experts models. Neural Computation, 28 (12), 2585-2593. doi: 10.1162/NECO_a_00892
Lloyd-Jones, Luke R., Nguyen, Hien D., Mclachlan, Geoﬀrey J., Sumpton, Wayne and Wang, You-Gan (2016). Mixture of time-dependent growth models with an application to blue swimmer crab length-frequency data. Biometrics, 72 (4), 1255-1265. doi: 10.1111/biom.12531
Progress on a conjecture regarding the triangular distribution
Nguyen, Hien D. and McLachlan, Geoffrey J. (2016). Progress on a conjecture regarding the triangular distribution. Communications in Statistics: Theory and Methods, 46 (22), 11261-11271. doi: 10.1080/03610926.2016.1263742
Linear mixed models with marginally symmetric nonparametric random effects
Nguyen, Hien D. and McLachlan, Geoffrey J. (2016). Linear mixed models with marginally symmetric nonparametric random effects. Computational Statistics and Data Analysis, 103, 151-169. doi: 10.1016/j.csda.2016.05.005
Spatial clustering of time series via mixture of autoregressions models and Markov random fields
Nguyen, Hien D., McLachlan, Geoffrey J., Ullmann, Jeremy F. P. and Janke, Andrew L. (2016). Spatial clustering of time series via mixture of autoregressions models and Markov random fields. Statistica Neerlandica, 70 (4), 414-439. doi: 10.1111/stan.12093
Maximum likelihood estimation of triangular and polygonal distributions
Nguyen, Hien D. and McLachlan, Geoffrey J. (2016). Maximum likelihood estimation of triangular and polygonal distributions. Computational Statistics and Data Analysis, 102, 23-36. doi: 10.1016/j.csda.2016.04.003
A block minorization-maximization algorithm for heteroscedastic regression
Nguyen, Hien D., Lloyd-Jones, Luke R. and McLachlan, Geoffrey J. (2016). A block minorization-maximization algorithm for heteroscedastic regression. IEEE Signal Processing Letters, 23 (8) 7501879, 1131-1135. doi: 10.1109/LSP.2016.2586180
Asymptotic normality of the maximum pseudolikelihood estimator for fully visible boltzmann machines
Nguyen, Hien D. and Wood, Ian A. (2016). Asymptotic normality of the maximum pseudolikelihood estimator for fully visible boltzmann machines. IEEE Transactions on Neural Networks and Learning Systems, 27 (4) 7103361, 897-902. doi: 10.1109/TNNLS.2015.2425898
Nguyen, Hien D. and Wood, Ian A. (2016). A block successive lower-bound maximization algorithm for the maximum pseudo-likelihood estimation of fully visible Boltzmann machines. Neural Computation, 28 (3), 485-492. doi: 10.1162/NECO_a_00813
Laplace mixture autoregressive models
Nguyen, Hien D., McLachlan, Geoffrey J., Ullmann, Jeremy F. P. and Janke, Andrew L. (2016). Laplace mixture autoregressive models. Statistics and Probability Letters, 110, 18-24. doi: 10.1016/j.spl.2015.11.006
Laplace mixture of linear experts
Nguyen, Hien D. and McLachlan, Geoffrey J. (2016). Laplace mixture of linear experts. Computational Statistics and Data Analysis, 93, 177-191. doi: 10.1016/j.csda.2014.10.016
Mixtures of spatial spline regressions for clustering and classification
Nguyen, Hien D., McLachlan, Geoffrey J. and Wood, Ian A. (2016). Mixtures of spatial spline regressions for clustering and classification. Computational Statistics and Data Analysis, 93, 76-85. doi: 10.1016/j.csda.2014.01.011
Maximum likelihood estimation of Gaussian mixture models without matrix operations
Nguyen, Hien D. and McLachlan, Geoffrey J. (2015). Maximum likelihood estimation of Gaussian mixture models without matrix operations. Advances in Data Analysis and Classification, 9 (4), 371-394. doi: 10.1007/s11634-015-0209-7
Improved estimation of size-transition matrices using tag-recapture data
Lloyd-Jones, Luke R., Nguyen, Hien D., Wang, You-Gan and O'Neill, Michael F. (2014). Improved estimation of size-transition matrices using tag-recapture data. Canadian Journal of Fisheries and Aquatic Sciences, 71 (9), 1385-1394. doi: 10.1139/cjfas-2014-0080
Chen, David, Shah, Anup, Nguyen, Hien, Loo, Dorothy, Inder, Kerry L. and Hill, Michelle M. (2014). Online quantitative proteomics p-value calculator for permutation-based statistical testing of peptide ratios. Journal of Proteome Research, 13 (9), 4184-4191. doi: 10.1021/pr500525e
False discovery rate control in magnetic resonance imaging studies via Markov random fields
Nguyen, Hien D., McLachlan, Geoffrey J., Cherbuin, Nicolas and Janke, Andrew L. (2014). False discovery rate control in magnetic resonance imaging studies via Markov random fields. IEEE Transactions on Medical Imaging, 33 (8) 6811158, 1735-1748. doi: 10.1109/TMI.2014.2322369
A robust permutation test for quantitative SILAC proteomics experiments
Nguyen, Hien D., Wood, Ian and Hill, Michelle M. (2012). A robust permutation test for quantitative SILAC proteomics experiments. Journal of Integrated OMICS, 2 (2), 80-93. doi: 10.5584/jiomics.v2i2.109
Inder, Kerry L., Zheng, Yu Zi, Davis, Melissa J., Moon, Hyeongsun, Loo, Dorothy, Nguyen, Hien, Clements, Judith A., Parton, Robert G., Foster, Leonard J. and Hill, Michelle M. (2012). Expression of PTRF in PC-3 cells modulates cholesterol dynamics and the actin cytoskeleton impacting secretion pathways. Molecular and Cellular Proteomics, 11 (2) M111.012245, M111.012245. doi: 10.1074/mcp.M111.012245
Murdoch, Bruce E. (2008). Preface. Communication Disorders in Childhood Cancer, 1150 CCIS, vii-viii. doi: 10.1002/9780470699232
K-means on positive definite matrices, and an application to clustering in radar image sequences
Fryer, Daniel, Nguyen, Hien and Castellazzi, Pascal (2020). K-means on positive definite matrices, and an application to clustering in radar image sequences. 2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020, Virtual, Canberra, 1-4 December 2020. IEEE. doi: 10.1109/SSCI47803.2020.9308185
An introduction to approximate Bayesian computation
Nguyen, Hien D. (2019). An introduction to approximate Bayesian computation. Research School on Statistics and Data Science, Melbourne, VIC, Australia, 24-26 July 2019. Heidelberg, Germany: Springer. doi: 10.1007/978-981-15-1960-4_7
Positive data kernel density estimation via the LogKDE package for R
Jones, Andrew T., Nguyen, Hien D. and McLachlan, Geoffrey J. (2019). Positive data kernel density estimation via the LogKDE package for R. AusDM 2018: 16th Australasian Conference on Data Mining, Bahrurst, NSW, Australia, 28 - 30 November 2018. Singapore, Singapore: Springer Singapore. doi: 10.1007/978-981-13-6661-1_21
Regularized Estimation and Feature Selection in Mixtures of Gaussian-Gated Experts Models
Chamroukhi, Faïcel, Lecocq, Florian and Nguyen, Hien D. (2019). Regularized Estimation and Feature Selection in Mixtures of Gaussian-Gated Experts Models. Research School on Statistics and Data Science 2019, Melbourne, VIC Australia, 24-26 July 2019. Heidelberg, Germany: Springer. doi: 10.1007/978-981-15-1960-4_3
A two-sample Kolmogorov-Smirnov-like test for big data
Nguyen, Hien D. (2018). A two-sample Kolmogorov-Smirnov-like test for big data. 15th Australasian Conference on Data Mining, AusDM 2017, Melbourne, Australia, 19-20 August 2017. Springer Verlag. doi: 10.1007/978-981-13-0292-3_6
Nguyen, Hien D. and McLachlan, Geoffrey J. (2017). Iteratively-reweighted least-squares fitting of support vector machines: a majorization–minimization algorithm approach. Future Technologies Conference (FTC) 2017, Vancouver, Canada, 29-30 November 2017. Piscataway, NJ United States: IEEE.
Asymptotic inference for hidden process regression models
Nguyen, Hien D. and McLachlan, Geoffrey J. (2014). Asymptotic inference for hidden process regression models. 2014 IEEE Workshop on Statistical Signal Processing (SSP 2014), Gold Coast, Australia, 29 June - 2 July 2014. Piscataway, NJ, United States: IEEE. doi: 10.1109/SSP.2014.6884624
Spatial false discovery rate control for magnetic resonance imaging studies
Nguyen, Hien D., McLachlan, Geoffrey J., Janke, Andrew L., Cherbuin, Nicolas, Sachdev, Perminder and Anstey, Kaarin J. (2013). Spatial false discovery rate control for magnetic resonance imaging studies. International Conference on Digital Image Computing: Techniques and Applications, DICTA 2013, Hobart, TAS, 26 - 28 November 2013. Piscataway, NJ United States: I E E E. doi: 10.1109/DICTA.2013.6691531
Nguyen, Hien D. and Wood, Ian A. (2012). Variable selection in statistical models using population-based incremental learning with applications to genome-wide association studies. 2012 IEEE World Congress on Computational Intelligence (IEEE-WCCI 2012), Brisbane Australia, 10-15 June 2012. Piscataway NJ, United States: I E E E. doi: 10.1109/CEC.2012.6256577
Finite mixture models for regression problems
Nguyen, Hien (2015). Finite mixture models for regression problems. PhD Thesis, School of Mathematics and Physics, The University of Queensland. doi: 10.14264/uql.2015.584
Stochastic majorization--minimization algorithms for data science
(2023–2026) ARC Discovery Projects
Feasible algorithms for big inference
(2021) ARC Discovery Early Career Researcher Award
Classification methods for providing personalised and class decisions
(2018–2022) ARC Discovery Projects
Feasible Algorithms for Big Inference
(2017) ARC Discovery Early Career Researcher Award
2015 AK Head Travelling Scholarship for Mathematical Scientists
(2014–2015) AK Head Travelling Scholarship for Mathematical Scientists
Deep learning approaches to the modelling of neuroimaging and neuroactivation data
Doctor Philosophy — Principal Advisor
Other advisors: