Hien Duy Nguyen
Orcid: 0000-0002-9958-432XAffiliations:
- La Trobe University, Bundoora, Australia
- The University of Queensland, St. Lucia, QLD, Australia (former)
According to our database1,
Hien Duy Nguyen
authored at least 47 papers
between 2012 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
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Online presence:
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on orcid.org
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on github.com
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on d-nb.info
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Bibliography
2024
Risk Bounds for Mixture Density Estimation on Compact Domains via the <i>h</i>-Lifted Kullback-Leibler Divergence.
CoRR, 2024
Proceedings of the International Joint Conference on Neural Networks, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Beyond Factualism: A Study of LLM Calibration Through the Lens of Conversational Emotion Recognition.
Proceedings of the AI 2024: Advances in Artificial Intelligence, 2024
2023
A Non-asymptotic Risk Bound for Model Selection in a High-Dimensional Mixture of Experts via Joint Rank and Variable Selection.
Proceedings of the AI 2023: Advances in Artificial Intelligence, 2023
2022
Summary statistics and discrepancy measures for approximate Bayesian computation via surrogate posteriors.
Stat. Comput., 2022
2021
Model independent feature attributions: Shapley values that uncover non-linear dependencies.
PeerJ Comput. Sci., 2021
A non-asymptotic model selection in block-diagonal mixture of polynomial experts models.
CoRR, 2021
A non-asymptotic penalization criterion for model selection in mixture of experts models.
CoRR, 2021
IEEE Access, 2021
2020
The fully visible Boltzmann machine and the Senate of the 45th Australian Parliament in 2016.
J. Comput. Soc. Sci., 2020
Frontiers Appl. Math. Stat., 2020
Bayesian clustering of skewed and multimodal data using geometric skewed normal distributions.
Comput. Stat. Data Anal., 2020
An l<sub>1</sub>-oracle inequality for the Lasso in mixture-of-experts regression models.
CoRR, 2020
Explaining the data or explaining a model? Shapley values that uncover non-linear dependencies.
CoRR, 2020
k-means on Positive Definite Matrices, and an Application to Clustering in Radar Image Sequences.
Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020
2019
WIREs Data Mining Knowl. Discov., 2019
BoltzMM: an R package for maximum pseudolikelihood estimation of fully-visible Boltzmann machines.
J. Open Source Softw., 2019
J. Open Source Softw., 2019
Approximation results regarding the multiple-output Gaussian gated mixture of linear experts model.
Neurocomputing, 2019
Regularized Estimation and Feature Selection in Mixtures of Gaussian-Gated Experts Models.
CoRR, 2019
2018
WIREs Data Mining Knowl. Discov., 2018
Whole-volume clustering of time series data from zebrafish brain calcium images via mixture modeling.
Stat. Anal. Data Min., 2018
Inf. Sci., 2018
A globally convergent algorithm for lasso-penalized mixture of linear regression models.
Comput. Stat. Data Anal., 2018
Proceedings of the Data Mining - 16th Australasian Conference, AusDM 2018, Bahrurst, NSW, 2018
2017
An introduction to Majorization-Minimization algorithms for machine learning and statistical estimation.
WIREs Data Mining Knowl. Discov., 2017
Neural Comput., 2017
Iteratively-Reweighted Least-Squares Fitting of Support Vector Machines: A Majorization-Minimization Algorithm Approach.
CoRR, 2017
An Introduction to the Practical and Theoretical Aspects of Mixture-of-Experts Modeling.
CoRR, 2017
Proceedings of the Data Mining, 2017
2016
Asymptotic Normality of the Maximum Pseudolikelihood Estimator for Fully Visible Boltzmann Machines.
IEEE Trans. Neural Networks Learn. Syst., 2016
IEEE Signal Process. Lett., 2016
A Block Successive Lower-Bound Maximization Algorithm for the Maximum Pseudo-Likelihood Estimation of Fully Visible Boltzmann Machines.
Neural Comput., 2016
Neural Comput., 2016
Comput. Stat. Data Anal., 2016
Comput. Stat. Data Anal., 2016
Comput. Stat. Data Anal., 2016
2015
Adv. Data Anal. Classif., 2015
2014
False Discovery Rate Control in Magnetic Resonance Imaging Studies via Markov Random Fields.
IEEE Trans. Medical Imaging, 2014
Proceedings of the IEEE Workshop on Statistical Signal Processing, 2014
2013
Proceedings of the 2013 International Conference on Digital Image Computing: Techniques and Applications, 2013
2012
Variable selection in statistical models using population-based incremental learning with applications to genome-wide association studies.
Proceedings of the IEEE Congress on Evolutionary Computation, 2012