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2023 Conference Publication Using cellular composition estimated from bulk RNA-seq data to suggest cellular level markers for melanoma survivalZhang, Min, Basford, Kaye, Arief, Vivi, McLachlan, Geoff and Nguyen, Quan (2023). Using cellular composition estimated from bulk RNA-seq data to suggest cellular level markers for melanoma survival. IBS-AR/SEEM Conference, Bay of Islands, Aotearoa, New Zealand, 27 November - 1 December 2023. |
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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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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 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 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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2020 Conference Publication Modelling asset return using multivariate asymmetric mixture models with applications to estimation of Value-at-RiskLee, Sharon X. and McLachlan, Geoffrey J. (2020). Modelling asset return using multivariate asymmetric mixture models with applications to estimation of Value-at-Risk. 20th International Congress on Modelling and Simulation - Adapting to Change: The Multiple Roles of Modelling, MODSIM 2013 , Adelaide, SA, Australia, 1 - 6 December 2013. Modelling and Simulation Society of Australia and New Zealand Inc. (MSSANZ). |
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2019 Conference Publication PPEM: privacy-preserving EM learning for mixture modelsLee, Sharon X., Leemaqz, Kaleb L. and McLachlan, Geoffrey J. (2019). PPEM: privacy-preserving EM learning for mixture models. 8th International Conference on Applications and Techniques in Information Security, ATIS 2017, Auckland, New Zealand, 6-7 July 2017. Oxford, United Kingdom: John Wiley & Sons. doi: 10.1002/cpe.5208 |
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2019 Conference Publication Flexible modelling via multivariate skew distributionsMcLachlan, Geoffrey J. and Lee, Sharon X. (2019). Flexible modelling via multivariate skew distributions. Research School on Statistics and Data Science (RSSDS 2019), Melbourne, VIC, Australia, 24–26 July 2019. Singapore, Singapore: Springer Singapore. doi: 10.1007/978-981-15-1960-4_4 |
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2019 Conference Publication Positive data kernel density estimation via the LogKDE package for RJones, 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 |
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2017 Conference Publication Corruption-resistant privacy preserving distributed EM algorithm for model-based clusteringLeemaqz, Kaleb L., Lee, Sharon X. and McLachlan, Geoffrey J. (2017). Corruption-resistant privacy preserving distributed EM algorithm for model-based clustering. 2017 IEEE Trustcom/BigDataSE/ICESS, Sydney, NSW, Australia, 1 - 4 August 2017. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/Trustcom/BigDataSE/ICESS.2017.356 |
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2017 Conference Publication Iteratively-reweighted least-squares fitting of support vector machines: a majorization–minimization algorithm approachNguyen, 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. |
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2017 Conference Publication On the identification of correlated differential features for supervised classification of high-dimensional dataNg, Shu Kay and McLachlan, Geoffrey J. (2017). On the identification of correlated differential features for supervised classification of high-dimensional data. 15th Conference of the International Federation of Classification Societies (IFCS), Bologna, Italy, July 5-8, 2015. Cham, Switzerland: Springer. doi: 10.1007/978-3-319-55723-6_4 |
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2017 Conference Publication Privacy distributed three-party learning of Gaussian mixture modelsLeemaqz, Kaleb L., Lee, Sharon X. and McLachlan, Geoffrey J. (2017). Privacy distributed three-party learning of Gaussian mixture models. International Conference on Applications and Technologies in Information Security (ATIS), Auckland, New Zealand, 6-7 July 2017. Singapore: Springer Singapore. doi: 10.1007/978-981-10-5421-1_7 |
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2016 Conference Publication On mixture modelling with multivariate skew distributionsLee, Sharon X. and McLachlan, Geoffrey J. (2016). On mixture modelling with multivariate skew distributions. COMPSTAT: International Conference on Computational Statistics, Oviedo, Spain, 23-26 August 2016. The Hague, The Netherlands: The International Statistical Institute/International Association for Statistical Computing. |
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2016 Conference Publication Finding group structures in "Big Data" in healthcare research using mixture modelsNg, Shu-Kay and McLachlan, Geoffrey J. (2016). Finding group structures in "Big Data" in healthcare research using mixture models. IEEE International Conference on Bioinformatics and Biomedicine, Shenzhen, China, 15-18 December 2016. Piscataway, NJ, United States: IEE Computer Society. doi: 10.1109/BIBM.2016.7822692 |
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2016 Conference Publication Robust estimation of mixtures of skew-normal distributionsGarcía-Escudero, L. A., Greselin, F., Mayo-Iscar, A. and McLachlan, G. J. (2016). Robust estimation of mixtures of skew-normal distributions. Scientific Meeting of the Italian Statistical Society, Salerno, Italy, 8-10 November 2016. Fisciano, Italy: Dipartimento di Scienze Economiche e Statistiche, University of Salerno.. |
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2016 Conference Publication A simple parallel EM algorithm for statistical learning via mixture modelsLee, Sharon X., Leemaqz, Kaleb L. and McLachlan, Geoffrey J. (2016). A simple parallel EM algorithm for statistical learning via mixture models. International Conference on Digital Image Computing, Gold Coast, QLD, Australia, 30 November - 2 December,2016. Piscataway, NJ, United States: IEEE (Institute for Electrical and Electronic Engineers). doi: 10.1109/DICTA.2016.7796997 |
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2016 Conference Publication Unsupervised component-wise EM learning for finite mixtures of skew t-distributionsLee, Sharon X. and McLachlan, Geoffrey J. (2016). Unsupervised component-wise EM learning for finite mixtures of skew t-distributions. 12th International Conference, ADMA 2016, Gold Coast, QLD, Australia, 12-15 December 2016. New York, NY, United States: Springer. doi: 10.1007/978-3-319-49586-6_49 |
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2014 Conference Publication Making sense of a random world through statisticsMcLachlan, Geoff (2014). Making sense of a random world through statistics. AusDM 2014, Brisbane, QLD, Australia, 27-28 November 2014. Darlinghurst, NSW, Australia: Australian Computer Society. |
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2014 Conference Publication Application of multiple imputation to incomplete three-way three-mode multi-environment trial dataTian, T., McLachlan, G., Dieters, M. and Basford, K. (2014). Application of multiple imputation to incomplete three-way three-mode multi-environment trial data. International Biometric Conference, Florence (Italy), 6-11 July 2014. Florence, Italy: International Biometric Society. |
