Geoffrey J. McLachlan

ORCID

Publication Activity (10 Years)

Years Active: 1976-2024
Publications (10 Years): 44

Top Venues

Comput. Stat. Data Anal.

CoRR

Stat. Comput.

Stat. Anal. Data Min.

Publications

Faïcel Chamroukhi, Nhat Thien Pham, Van Hà Hoang, Geoffrey J. McLachlan
Functional mixtures-of-experts. Stat. Comput. 34 (3) (2024)
You-Gan Wang, Jinran Wu, Zhi-Hua Hu, Geoffrey J. McLachlan
A new algorithm for support vector regression with automatic selection of hyperparameters. Pattern Recognit. 133 (2023)
Sharon X. Lee, Geoffrey J. McLachlan
An overview of skew distributions in model-based clustering. J. Multivar. Anal. 188 (2022)
Faïcel Chamroukhi, Nhat Thien Pham, Van Hà Hoang, Geoffrey J. McLachlan
Functional Mixtures-of-Experts. CoRR (2022)
Ziyang Lyu, Daniel Ahfock, Geoffrey J. McLachlan
Some Simulation and Empirical Results for Semi-Supervised Learning of the Bayes Rule of Allocation. CoRR (2022)
Daniel Ahfock, Saumyadipta Pyne, Geoffrey J. McLachlan
Statistical file-matching of non-Gaussian data: A game theoretic approach. Comput. Stat. Data Anal. 168 (2022)
Daniel Ahfock, Geoffrey J. McLachlan
Harmless label noise and informative soft-labels in supervised classification. CoRR (2021)
Sharon X. Lee, Geoffrey J. McLachlan, Kaleb L. Leemaqz
Multi-node Expectation-Maximization algorithm for finite mixture models. Stat. Anal. Data Min. 14 (4) (2021)
Daniel Ahfock, Geoffrey J. McLachlan
Harmless label noise and informative soft-labels in supervised classification. Comput. Stat. Data Anal. 161 (2021)
Daniel Ahfock, Geoffrey J. McLachlan
Semi-Supervised Learning of Classifiers from a Statistical Perspective: A Brief Review. CoRR (2021)
Mohadeseh Alsadat Farzammehr, Mohammad Reza Zadkarami, Geoffrey J. McLachlan
Skew-normal generalized spatial panel data model. Commun. Stat. Simul. Comput. 50 (11) (2021)
Sharon X. Lee, Tsung-I Lin, Geoffrey J. McLachlan
Mixtures of factor analyzers with scale mixtures of fundamental skew normal distributions. Adv. Data Anal. Classif. 15 (2) (2021)
Daniel Ahfock, Saumyadipta Pyne, Geoffrey J. McLachlan
Data fusion using factor analysis and low-rank matrix completion. Stat. Comput. 31 (5) (2021)
Geoffrey J. McLachlan, Daniel Ahfock
Estimation of Classification Rules from Partially Classified Data. CoRR (2020)
Daniel Ahfock, Geoffrey J. McLachlan
An apparent paradox: a classifier based on a partially classified sample may have smaller expected error rate than that if the sample were completely classified. Stat. Comput. 30 (6) (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)
Sharon X. Lee, Kaleb L. Leemaqz, Geoffrey J. McLachlan
PPEM: Privacy-preserving EM learning for mixture models. Concurr. Comput. Pract. Exp. 31 (24) (2019)
Shu-Kay Ng, Richard Tawiah, Geoffrey J. McLachlan
Unsupervised pattern recognition of mixed data structures with numerical and categorical features using a mixture regression modelling framework. Pattern Recognit. 88 (2019)
Cinzia Viroli, Geoffrey J. McLachlan
Deep Gaussian mixture models. Stat. Comput. 29 (1) (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)
Sharon X. Lee, Kaleb L. Leemaqz, Geoffrey J. McLachlan
A Block EM Algorithm for Multivariate Skew Normal and Skew $t$ -Mixture Models. IEEE Trans. Neural Networks Learn. Syst. 29 (11) (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 D. Nguyen, Andrew T. Jones, Geoffrey J. McLachlan
Positive Data Kernel Density Estimation via the LogKDE Package for R. AusDM (2018)
Cinzia Viroli, Geoffrey J. McLachlan
Deep Gaussian Mixture Models. CoRR (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)
Kaleb L. Leemaqz, Sharon X. Lee, Geoffrey J. McLachlan
Private Distributed Three-Party Learning of Gaussian Mixture Models. ATIS (2017)
Kaleb L. Leemaqz, Sharon X. Lee, Geoffrey J. McLachlan
Corruption-Resistant Privacy Preserving Distributed EM Algorithm for Model-Based Clustering. TrustCom/BigDataSE/ICESS (2017)
Hien D. Nguyen, Geoffrey J. McLachlan
Iteratively-Reweighted Least-Squares Fitting of Support Vector Machines: A Majorization-Minimization Algorithm Approach. CoRR (2017)
Hien Duy Nguyen, Geoffrey J. McLachlan
Laplace mixture of linear experts. Comput. Stat. Data Anal. 93 (2016)
Daniel Ahfock, Saumyadipta Pyne, Sharon X. Lee, Geoffrey J. McLachlan
Partial identification in the statistical matching problem. Comput. Stat. Data Anal. 104 (2016)
Sharon X. Lee, Geoffrey J. McLachlan
Unsupervised Component-Wise EM Learning for Finite Mixtures of Skew t-distributions. ADMA (2016)
Hien Duy Nguyen, Geoffrey J. McLachlan
Maximum likelihood estimation of triangular and polygonal distributions. Comput. Stat. Data Anal. 102 (2016)
Sharon X. Lee, Kaleb L. Leemaqz, Geoffrey J. McLachlan
A block EM algorithm for multivariate skew normal and skew t-mixture models. CoRR (2016)
Tsung-I Lin, Geoffrey J. McLachlan, Sharon X. Lee
Extending mixtures of factor models using the restricted multivariate skew-normal distribution. J. Multivar. Anal. 143 (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)
Shu-Kay Ng, Geoffrey J. McLachlan
Finding group structures in "Big Data" in healthcare research using mixture models. BIBM (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)
Sharon X. Lee, Kaleb L. Leemaqz, Geoffrey J. McLachlan
A Simple Parallel EM Algorithm for Statistical Learning via Mixture Models. DICTA (2016)
Sharon X. Lee, Geoffrey J. McLachlan
Finite mixtures of canonical fundamental skew t-distributions - The unification of the restricted and unrestricted skew t-mixture models. Stat. Comput. 26 (3) (2016)
Hien Duy Nguyen, Geoffrey J. McLachlan
Maximum likelihood estimation of Gaussian mixture models without matrix operations. Adv. Data Anal. Classif. 9 (4) (2015)
Shu-Kay Ng, Geoffrey J. McLachlan
Mixture models for clustering multilevel growth trajectories. Comput. Stat. Data Anal. 71 (2014)
Geoffrey J. McLachlan, Suren I. Rathnayake
On the number of components in a Gaussian mixture model. WIREs Data Mining Knowl. Discov. 4 (5) (2014)
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)
Sharon X. Lee, Geoffrey J. McLachlan
Finite mixtures of multivariate skew t-distributions: some recent and new results. Stat. Comput. 24 (2) (2014)
Dankmar Böhning, Christian Hennig, Geoffrey J. McLachlan, Paul D. McNicholas
The 2nd special issue on advances in mixture models. Comput. Stat. Data Anal. 71 (2014)
Mingzhu Sun, Geoffrey J. McLachlan
A common factor-analytic model for classification. BIBM (2013)
Kaye E. Basford, Geoffrey J. McLachlan, Suren I. Rathnayake
On the classification of microarray gene-expression data. Briefings Bioinform. 14 (4) (2013)
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)
Sharon X. Lee, Geoffrey J. McLachlan
On mixtures of skew normal and skew t-distributions. Adv. Data Anal. Classif. 7 (3) (2013)
Sharon X. Lee, Geoffrey J. McLachlan
Rejoinder to the discussion of "Model-based clustering and classification with non-normal mixture distributions". Stat. Methods Appl. 22 (4) (2013)
Sharon X. Lee, Geoffrey J. McLachlan
Model-based clustering and classification with non-normal mixture distributions. Stat. Methods Appl. 22 (4) (2013)
Shu-Kay Ng, Geoffrey J. McLachlan
Using cluster analysis to improve gene selection in the formation of discriminant rules for the prediction of disease outcomes. BIBM (2013)
Kui Wang, Shu-Kay Ng, Geoffrey J. McLachlan
Clustering of time-course gene expression profiles using normal mixture models with autoregressive random effects. BMC Bioinform. 13 (2012)
Gabor Melli, Xindong Wu, Paul Beinat, Francesco Bonchi, Longbing Cao, Rong Duan, Christos Faloutsos, Rayid Ghani, Brendan Kitts, Bart Goethals, Geoffrey J. McLachlan, Jian Pei, Ashok Srivastava, Osmar R. Zaïane
Top-10 Data Mining Case Studies. Int. J. Inf. Technol. Decis. Mak. 11 (2) (2012)
Jangsun Baek, Geoffrey J. McLachlan
-factor analyzers for clustering high-dimensional microarray data. Bioinform. 27 (9) (2011)
Vladimir Nikulin, Tian-Hsiang Huang, Geoffrey J. McLachlan
Classification of High-Dimensional microarray Data with a Two-Step Procedure via a Wilcoxon Criterion and Multilayer Perceptron. Int. J. Comput. Intell. Appl. 10 (1) (2011)
Vladimir Nikulin, Geoffrey J. McLachlan
On the Gradient-based Algorithm for Matrix Factorization Applied to Dimensionality Reduction. BIOINFORMATICS (2010)
Geoffrey J. McLachlan
Assessing the Significance of Groups in High-Dimensional Data. ICDM (2010)
Vladimir Nikulin, Geoffrey J. McLachlan
Identifying fiber bundles with regularised к-means clustering applied to the grid-based data. IJCNN (2010)
Vladimir Nikulin, Tian-Hsiang Huang, Shu-Kay Ng, Suren I. Rathnayake, Geoffrey J. McLachlan
A Very Fast Algorithm for Matrix Factorization CoRR (2010)
Kim-Anh Lê Cao, Emmanuelle Meugnier, Geoffrey J. McLachlan
Integrative mixture of experts to combine clinical factors and gene markers. Bioinform. 26 (9) (2010)
Vladimir Nikulin, Tian-Hsiang Huang, Geoffrey J. McLachlan
A comparative study of two matrix factorization methods applied to the classification of gene expression data. BIBM (2010)
Jangsun Baek, Geoffrey J. McLachlan, Lloyd K. Flack
Mixtures of Factor Analyzers with Common Factor Loadings: Applications to the Clustering and Visualization of High-Dimensional Data. IEEE Trans. Pattern Anal. Mach. Intell. 32 (7) (2010)
Saumyadipta Pyne, Xinli Hu, Kui Wang, Elizabeth Rossin, Tsung-I Lin, Lisa Maier, Clare Baecher-Allan, Geoffrey J. McLachlan, Pablo Tamayo, David Hafler, Philip L. De Jager, Jill P. Mesirov
Automated High-Dimensional Flow Cytometric Data Analysis. RECOMB (2010)
Kui Wang, Shu-Kay Ng, Geoffrey J. McLachlan
Multivariate Skew t Mixture Models: Applications to Fluorescence-Activated Cell Sorting Data. DICTA (2009)
Vladimir Nikulin, Geoffrey J. McLachlan
Penalized Principal Component Analysis of Microarray Data. CIBB (2009)
Vladimir Nikulin, Geoffrey J. McLachlan
Classification of Imbalanced Marketing Data with Balanced Random Sets. KDD Cup (2009)
Vladimir Nikulin, Geoffrey J. McLachlan, Shu-Kay Ng
Ensemble Approach for the Classification of Imbalanced Data. Australasian Conference on Artificial Intelligence (2009)
Xindong Wu, Vipin Kumar, J. Ross Quinlan, Joydeep Ghosh, Qiang Yang, Hiroshi Motoda, Geoffrey J. McLachlan, Angus F. M. Ng, Bing Liu, Philip S. Yu, Zhi-Hua Zhou, Michael S. Steinbach, David J. Hand, Dan Steinberg
Top 10 algorithms in data mining. Knowl. Inf. Syst. 14 (1) (2008)
Geoffrey J. McLachlan, Jangsun Baek
Clustering of High-Dimensional Data via Finite Mixture Models. GfKl (2008)
Murray A. Jorgensen, Geoffrey J. McLachlan
Wallace's Approach to Unsupervised Learning: The Snob Program. Comput. J. 51 (5) (2008)
Jangsun Baek, Young Sook Son, Geoffrey J. McLachlan
Segmentation and intensity estimation of microarray images using a gamma-t mixture model. Bioinform. 23 (4) (2007)
Vladimir Nikulin, Geoffrey J. McLachlan
Merging Algorithm to Reduce Dimensionality in Application to Web-Mining. Australian Conference on Artificial Intelligence (2007)
Geoffrey J. McLachlan, Richard W. Bean, Liat Ben-Tovim Jones
Extension of the mixture of factor analyzers model to incorporate the multivariate t-distribution. Comput. Stat. Data Anal. 51 (11) (2007)
Kui Wang, Kelvin K. W. Yau, Andy H. Lee, Geoffrey J. McLachlan
Two-component Poisson mixture regression modelling of count data with bivariate random effects. Math. Comput. Model. 46 (11-12) (2007)
Kui Wang, Kelvin K. W. Yau, Andy H. Lee, Geoffrey J. McLachlan
Multilevel survival modelling of recurrent urinary tract infections. Comput. Methods Programs Biomed. 87 (3) (2007)
Shu-Kay Ng, Geoffrey J. McLachlan
Extension of mixture-of-experts networks for binary classification of hierarchical data. Artif. Intell. Medicine 41 (1) (2007)
Shu-Kay Ng, Geoffrey J. McLachlan, Andy H. Lee
An incremental EM-based learning approach for on-line prediction of hospital resource utilization. Artif. Intell. Medicine 36 (3) (2006)
Liat Ben-Tovim Jones, Richard Bean, Geoffrey J. McLachlan, Justin Xi Zhu
Mixture Models for Detecting Differentially Expressed Genes in Microarrays. Int. J. Neural Syst. 16 (5) (2006)
Shu-Kay Ng, Geoffrey J. McLachlan, Kui Wang, Liat Ben-Tovim Jones, S.-W. Ng
A Mixture model with random-effects components for clustering correlated gene-expression profiles. Bioinform. 22 (14) (2006)
Geoffrey J. McLachlan, Richard W. Bean, Liat Ben-Tovim Jones
A simple implementation of a normal mixture approach to differential gene expression in multiclass microarrays. Bioinform. 22 (13) (2006)
Richard Bean, Geoffrey J. McLachlan
Cluster Analysis of High-Dimensional Data: A Case Study. IDEAL (2005)
Liat Ben-Tovim Jones, Richard Bean, Geoffrey J. McLachlan, Justin Xi Zhu
Application of Mixture Models to Detect Differentially Expressed Genes. IDEAL (2005)
Shu-Kay Ng, Geoffrey J. McLachlan
Normalized Gaussian Networks with Mixed Feature Data. Australian Conference on Artificial Intelligence (2005)
Shu-Kay Ng, Geoffrey J. McLachlan
Using the EM algorithm to train neural networks: misconceptions and a new algorithm for multiclass classification. IEEE Trans. Neural Networks 15 (3) (2004)
Shu-Kay Ng, Geoffrey J. McLachlan
Speeding up the EM algorithm for mixture model-based segmentation of magnetic resonance images. Pattern Recognit. 37 (8) (2004)
Geoffrey J. McLachlan, Soong Chang, Jess Mar, Christophe Ambroise, Justin Xi Zhu
On the Simultaneous Use of Clinical and Microarray Expression Data in the Cluster Analysis of Tissue Samples. APBC (2004)
J. C. Mar, Geoffrey J. McLachlan
Model-Based Clustering In Gene Expression Microarrays: An Application To Breast Cancer Data. Int. J. Softw. Eng. Knowl. Eng. 13 (6) (2003)
Geoffrey J. McLachlan, David Peel, Richard W. Bean
Modelling high-dimensional data by mixtures of factor analyzers. Comput. Stat. Data Anal. 41 (3-4) (2003)
J. C. Mar, Geoffrey J. McLachlan
Model-Based Clustering in Gene Expression Microarrays: An Application to Breast Cancer Data. APBC (2003)
Shu-Kay Ng, Geoffrey J. McLachlan
On the choice of the number of blocks with the incremental EM algorithm for the fitting of normal mixtures. Stat. Comput. 13 (1) (2003)
Shu-Kay Ng, Geoffrey J. McLachlan
Robust Estimation in Gaussian Mixtures Using Multiresolution Kd-trees. DICTA (2003)
Igor V. Cadez, Padhraic Smyth, Geoffrey J. McLachlan, Christine E. McLaren
Maximum Likelihood Estimation of Mixture Densities for Binned and Truncated Multivariate Data. Mach. Learn. 47 (1) (2002)
Geoffrey J. McLachlan, Richard W. Bean, David Peel
A mixture model-based approach to the clustering of microarray expression data. Bioinform. 18 (3) (2002)

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Publication Activity (10 Years)

Top Topics

Top Venues

Geoffrey J. McLachlan