Hien Duy Nguyen

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 27

Top Topics

Model Selection

Density Estimation

Maximum Likelihood Estimation

Top Venues

Comput. Stat. Data Anal.

WIREs Data Mining Knowl. Discov.

Publications

Mark Chiu Chong, Hien Duy Nguyen, TrungTin Nguyen
-Lifted Kullback-Leibler Divergence. CoRR (2024)
TrungTin Nguyen, Dung Ngoc Nguyen, Hien Duy Nguyen, Faicel Chamroukhi
A Non-asymptotic Risk Bound for Model Selection in a High-Dimensional Mixture of Experts via Joint Rank and Variable Selection. AI (2) (2023)
Florence Forbes, Hien Duy Nguyen, TrungTin Nguyen, Julyan Arbel
Summary statistics and discrepancy measures for approximate Bayesian computation via surrogate posteriors. Stat. Comput. 32 (5) (2022)
TrungTin Nguyen, Faicel Chamroukhi, Hien Duy Nguyen, Florence Forbes
A non-asymptotic model selection in block-diagonal mixture of polynomial experts models. CoRR (2021)
TrungTin Nguyen, Hien Duy Nguyen, Faicel Chamroukhi, Florence Forbes
A non-asymptotic penalization criterion for model selection in mixture of experts models. CoRR (2021)
Hien Duy Nguyen, Julyan Arbel, Hongliang Lü, Florence Forbes
Approximate Bayesian Computation Via the Energy Statistic. IEEE Access 8 (2020)
Edoardo Redivo, Hien Duy Nguyen, Mayetri Gupta
Bayesian clustering of skewed and multimodal data using geometric skewed normal distributions. Comput. Stat. Data Anal. 152 (2020)
Hien Duy Nguyen, Florence Forbes, Geoffrey J. McLachlan
Mini-batch learning of exponential family finite mixture models. Stat. Comput. 30 (4) (2020)
TrungTin Nguyen, Hien Duy Nguyen, Faicel Chamroukhi, Geoffrey J. McLachlan
-oracle inequality for the Lasso in mixture-of-experts regression models. CoRR (2020)
Faicel Chamroukhi, Hien Duy Nguyen
Model-based clustering and classification of functional data. WIREs Data Mining Knowl. Discov. 9 (4) (2019)
Andrew T. Jones, Jessica Bagnall, Hien Duy Nguyen
BoltzMM: an R package for maximum pseudolikelihood estimation of fully-visible Boltzmann machines. J. Open Source Softw. 4 (34) (2019)
Hien Duy Nguyen, Dianhui Wang, Geoffrey J. McLachlan
Randomized mixture models for probability density approximation and estimation. Inf. Sci. 467 (2018)
Hien Duy Nguyen, Jeremy F. P. Ullmann, Geoffrey J. McLachlan, Venkatakaushik Voleti, Wenze Li, Elizabeth M. C. Hillman, David C. Reutens, Andrew L. Janke
Whole-volume clustering of time series data from zebrafish brain calcium images via mixture modeling. Stat. Anal. Data Min. 11 (1) (2018)
Hien Duy Nguyen, Faicel Chamroukhi
Practical and theoretical aspects of mixture-of-experts modeling: An overview. WIREs Data Mining Knowl. Discov. 8 (4) (2018)
Luke R. Lloyd-Jones, Hien Duy Nguyen, Geoffrey J. McLachlan
A globally convergent algorithm for lasso-penalized mixture of linear regression models. Comput. Stat. Data Anal. 119 (2018)
Andrew T. Jones, Hien Duy Nguyen, Geoffrey J. McLachlan
logKDE: log-transformed kernel density estimation. J. Open Source Softw. 3 (28) (2018)
Hien Duy Nguyen
A Two-Sample Kolmogorov-Smirnov-Like Test for Big Data. AusDM (2017)
Hien Duy Nguyen, Geoffrey J. McLachlan, Pierre Orban, Pierre Bellec, Andrew L. Janke
Maximum Pseudolikelihood Estimation for Model-Based Clustering of Time Series Data. Neural Comput. 29 (4) (2017)
Hien Duy Nguyen
An introduction to Majorization-Minimization algorithms for machine learning and statistical estimation. WIREs Data Mining Knowl. Discov. 7 (2) (2017)
Hien Duy Nguyen, Geoffrey J. McLachlan
Laplace mixture of linear experts. Comput. Stat. Data Anal. 93 (2016)
Hien Duy Nguyen, Ian A. Wood
A Block Successive Lower-Bound Maximization Algorithm for the Maximum Pseudo-Likelihood Estimation of Fully Visible Boltzmann Machines. Neural Comput. 28 (3) (2016)
Hien Duy Nguyen, Geoffrey J. McLachlan
Maximum likelihood estimation of triangular and polygonal distributions. Comput. Stat. Data Anal. 102 (2016)
Hien Duy Nguyen, Luke R. Lloyd-Jones, Geoffrey J. McLachlan
A Block Minorization-Maximization Algorithm for Heteroscedastic Regression. IEEE Signal Process. Lett. 23 (8) (2016)
Hien Duy Nguyen, Geoffrey J. McLachlan, Ian A. Wood
Mixtures of spatial spline regressions for clustering and classification. Comput. Stat. Data Anal. 93 (2016)
Hien Duy Nguyen, Geoffrey J. McLachlan
Linear mixed models with marginally symmetric nonparametric random effects. Comput. Stat. Data Anal. 103 (2016)
Hien Duy Nguyen, Luke R. Lloyd-Jones, Geoffrey J. McLachlan
A Universal Approximation Theorem for Mixture-of-Experts Models. Neural Comput. 28 (12) (2016)
Hien Duy Nguyen, Ian A. Wood
Asymptotic Normality of the Maximum Pseudolikelihood Estimator for Fully Visible Boltzmann Machines. IEEE Trans. Neural Networks Learn. Syst. 27 (4) (2016)
Hien Duy Nguyen, Geoffrey J. McLachlan
Maximum likelihood estimation of Gaussian mixture models without matrix operations. Adv. Data Anal. Classif. 9 (4) (2015)
Hien Duy Nguyen, Geoffrey J. McLachlan, Nicolas Cherbuin, Andrew L. Janke
False Discovery Rate Control in Magnetic Resonance Imaging Studies via Markov Random Fields. IEEE Trans. Medical Imaging 33 (8) (2014)
Hien Duy Nguyen, Geoffrey J. McLachlan
Asymptotic inference for hidden process regression models. SSP (2014)
Hien Duy Nguyen, Andrew L. Janke, Nicolas Cherbuin, Geoffrey J. McLachlan, Perminder S. Sachdev, Kaarin Anstey
Spatial False Discovery Rate Control for Magnetic Resonance Imaging Studies. DICTA (2013)
Hien Duy Nguyen, Ian A. Wood
Variable selection in statistical models using population-based incremental learning with applications to genome-wide association studies. IEEE Congress on Evolutionary Computation (2012)