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2022 Conference Publication Exploratory data analysis of TCGA skin cutaneous melanoma RNA-seq dataZhang, Min, Arief, Vivi, McLachlan, Geoffrey, Nguyen, Quan and Basford, Kaye (2022). Exploratory data analysis of TCGA skin cutaneous melanoma RNA-seq data. Australasian Applied Statistics Conference (AASC), Inverloch, VIC Australia, 28 November - 2 December 2022. |
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2022 Journal Article An Automated Machine learning (AutoML) approach to regression models in minerals processing with case studies of developing industrial comminution and flotation modelsKoh, Edwin J. Y., Amini, Eiman, Gaur, Shruti, Becerra Maquieira, Miguel, Jara Heck, Christian, McLachlan, Geoffrey J. and Beaton, Nick (2022). An Automated Machine learning (AutoML) approach to regression models in minerals processing with case studies of developing industrial comminution and flotation models. Minerals Engineering, 189 107886, 107886. doi: 10.1016/j.mineng.2022.107886 |
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2022 Journal Article A spatial heterogeneity mixed model with skew-elliptical distributionsFarzammehr, Mohadeseh Alsadat and McLachlan, Geoffrey J. (2022). A spatial heterogeneity mixed model with skew-elliptical distributions. Communications for Statistical Applications and Methods, 29 (3), 373-391. doi: 10.29220/csam.2022.29.3.373 |
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2022 Other Outputs Detecting accounting fraud with noisy labelsAhfock, Daniel, McLachlan, Geoffrey, Yang, Liu and Zhu, Min (2022). Detecting accounting fraud with noisy labels. UQ Business School. |
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2022 Journal Article Statistical file-matching of non-Gaussian data: a game theoretic approachAhfock, Daniel, Pyne, Saumyadipta and McLachlan, Geoffrey J. (2022). Statistical file-matching of non-Gaussian data: a game theoretic approach. Computational Statistics and Data Analysis, 168 107387, 1-16. doi: 10.1016/j.csda.2021.107387 |
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2022 Journal Article An overview of skew distributions in model-based clusteringLee, Sharon X. and McLachlan, Geoffrey J. (2022). An overview of skew distributions in model-based clustering. Journal of Multivariate Analysis, 188 104853, 1-14. doi: 10.1016/j.jmva.2021.104853 |
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2022 Book Chapter EM algorithmMcLachlan, Geoffrey J., Ng, Shu-Kay and Nguyen, Hien D. (2022). EM algorithm. Wiley StatsREF: statistics reference online. (pp. 1-19) edited by N. Balakrishnan, P. Brandimarte, B. Everitt, G. Molenberghs, F. Ruggeri and W. Piegorsch. Chichester, West Sussex, United Kingdom: Wiley. doi: 10.1002/9781118445112.stat00410.pub2 |
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2022 Journal Article Bayesian analysis of generalized linear mixed models with spatial correlated and unrestricted skew normal errorsFarzammehr, Mohadeseh Alsadat, Mohammadzadeh, Mohsen, Zadkarami, Mohammad Reza and McLachlan, Geoffrey J. (2022). Bayesian analysis of generalized linear mixed models with spatial correlated and unrestricted skew normal errors. Communications in Statistics: Theory and Methods, 51 (24), 8476-8498. doi: 10.1080/03610926.2021.1897843 |
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2021 Journal Article Approximations of conditional probability density functions in Lebesgue spaces via mixture of experts modelsNguyen, 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 |
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2021 Journal Article Utilising convolutional neural networks to perform fast automated modal mineralogy analysis for thin-section optical microscopyKoh, Edwin J. Y., Amini, Eiman, McLachlan, Geoffrey J. and Beaton, Nick (2021). Utilising convolutional neural networks to perform fast automated modal mineralogy analysis for thin-section optical microscopy. Minerals Engineering, 173 107230, 107230. doi: 10.1016/j.mineng.2021.107230 |
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2021 Conference Publication AEGC Machine Learning Workshop presentationChatterjee, Robindra, Valenta, Richard, McLachlan, Geoffrey and Weatherley, Dion (2021). AEGC Machine Learning Workshop presentation. Australian Exploration Geoscience Conference, Online, 14-17 September 2021. |
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2021 Journal Article Utilising a deep neural network as a surrogate model to approximate phenomenological models of a comminution circuit for faster simulationsKoh, Edwin J.Y., Amini, Eiman, McLachlan, Geoffrey J. and Beaton, Nick (2021). Utilising a deep neural network as a surrogate model to approximate phenomenological models of a comminution circuit for faster simulations. Minerals Engineering, 170 107026, 1-11. doi: 10.1016/j.mineng.2021.107026 |
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2021 Journal Article Data fusion using factor analysis and low-rank matrix completionAhfock, Daniel, Pyne, Saumyadipta and McLachlan, Geoffrey J. (2021). Data fusion using factor analysis and low-rank matrix completion. Statistics and Computing, 31 (5) 58. doi: 10.1007/s11222-021-10033-7 |
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2021 Journal Article Multi‐node expectation–maximization algorithm for finite mixture modelsLee, Sharon X., McLachlan, Geoffrey J. and Leemaqz, Kaleb L. (2021). Multi‐node expectation–maximization algorithm for finite mixture models. Statistical Analysis and Data Mining: The ASA Data Science Journal, 14 (4) sam.11529, 297-304. doi: 10.1002/sam.11529 |
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2021 Journal Article Harmless label noise and informative soft-labels in supervised classificationAhfock, Daniel and McLachlan, Geoffrey J. (2021). Harmless label noise and informative soft-labels in supervised classification. Computational Statistics and Data Analysis, 161 107253, 107253. doi: 10.1016/j.csda.2021.107253 |
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2021 Conference Publication Extending FaultSeg3D to Minerals Seismic: Part 1 – A synthetic 3D-seismic training-volume generator for preparing data replicating a hardrock terrane to train an automatic-fault-prediction algorithmChatterjee, Robindra , Valenta, Richard , McLachlan, Geoffrey and Weatherley, Dion (2021). Extending FaultSeg3D to Minerals Seismic: Part 1 – A synthetic 3D-seismic training-volume generator for preparing data replicating a hardrock terrane to train an automatic-fault-prediction algorithm. Australian Earth Science Convention, Virtual, 9-12 February 2021. |
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2021 Book Chapter Estimation of classification rules from partially classified dataMcLachlan, Geoffrey and Ahfock, Daniel (2021). Estimation of classification rules from partially classified data. Data analysis and rationality in a complex world. (pp. 149-157) edited by Theodore Chadjipadelis, Berthold Lausen, Angelos Markos, Tae Rim Lee, Angela Montanari and Rebecca Nugent. Cham, Switzerland: Springer. doi: 10.1007/978-3-030-60104-1_17 |
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2021 Journal Article On formulations of skew factor models: Skew factors and/or skew errorsLee, Sharon X. and McLachlan, Geoffrey J. (2021). On formulations of skew factor models: Skew factors and/or skew errors. Statistics and Probability Letters, 168 108935, 108935. doi: 10.1016/j.spl.2020.108935 |
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2021 Conference Publication On Mean And/or Variance Mixtures of Normal DistributionsLee, Sharon X. and McLachlan, Geoffrey J. (2021). On Mean And/or Variance Mixtures of Normal Distributions. 12th Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society (CLADAG 2019), Cassino, Italy, 11–13 September 2019. Cham, Switzerland: Springer. doi: 10.1007/978-3-030-69944-4_13 |
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2021 Book Chapter Automated gating and dimension reduction of high-dimensional cytometry dataLee, Sharon X., McLachlan, Geoffrey J. and Pyne, Saumyadipta (2021). Automated gating and dimension reduction of high-dimensional cytometry data. Mathematical, computational and experimental T cell immunology. (pp. 281-294) edited by Carmen Molina-París and Grant Lythe . Cham, Switzerland: Springer. doi: 10.1007/978-3-030-57204-4_16 |
