Geoffrey J. McLachlan

120 papers A* 4B 5C 3Misc 5Journal 84Unranked 15

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Informative missingness and its implications in semi-supervised learning. CoRR Jinran Wu, You-Gan Wang, Geoffrey J. McLachlan
2024	J	`jnl`	Functional mixtures-of-experts. Stat. Comput. Faïcel Chamroukhi, Nhat Thien Pham, Van Hà Hoang, Geoffrey J. McLachlan
2023	J	`jnl`	A new algorithm for support vector regression with automatic selection of hyperparameters. Pattern Recognit. You-Gan Wang, Jinran Wu, Zhi-Hua Hu, Geoffrey J. McLachlan
2022	J	`jnl`	An overview of skew distributions in model-based clustering. J. Multivar. Anal. Sharon X. Lee, Geoffrey J. McLachlan
2022	J	`jnl`	Functional Mixtures-of-Experts. CoRR Faïcel Chamroukhi, Nhat Thien Pham, Van Hà Hoang, Geoffrey J. McLachlan
2022	J	`jnl`	Some Simulation and Empirical Results for Semi-Supervised Learning of the Bayes Rule of Allocation. CoRR Ziyang Lyu, Daniel Ahfock, Geoffrey J. McLachlan
2022	J	`jnl`	Statistical file-matching of non-Gaussian data: A game theoretic approach. Comput. Stat. Data Anal. Daniel Ahfock, Saumyadipta Pyne, Geoffrey J. McLachlan
2021	J	`jnl`	Data fusion using factor analysis and low-rank matrix completion. Stat. Comput. Daniel Ahfock, Saumyadipta Pyne, Geoffrey J. McLachlan
2021	J	`jnl`	Harmless label noise and informative soft-labels in supervised classification. CoRR Daniel Ahfock, Geoffrey J. McLachlan
2021	J	`jnl`	Harmless label noise and informative soft-labels in supervised classification. Comput. Stat. Data Anal. Daniel Ahfock, Geoffrey J. McLachlan
2021	J	`jnl`	Mixtures of factor analyzers with scale mixtures of fundamental skew normal distributions. Adv. Data Anal. Classif. Sharon X. Lee, Tsung-I Lin, Geoffrey J. McLachlan
2021	J	`jnl`	Multi-node Expectation-Maximization algorithm for finite mixture models. Stat. Anal. Data Min. Sharon X. Lee, Geoffrey J. McLachlan, Kaleb L. Leemaqz
2021	J	`jnl`	Semi-Supervised Learning of Classifiers from a Statistical Perspective: A Brief Review. CoRR Daniel Ahfock, Geoffrey J. McLachlan
2021	J	`jnl`	Skew-normal generalized spatial panel data model. Commun. Stat. Simul. Comput. Mohadeseh Alsadat Farzammehr, Mohammad Reza Zadkarami, Geoffrey J. McLachlan
2020	J	`jnl`	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. Daniel Ahfock, Geoffrey J. McLachlan
2020	J	`jnl`	An l CoRR TrungTin Nguyen, Hien Duy Nguyen, Faicel Chamroukhi, Geoffrey J. McLachlan
2020	J	`jnl`	Estimation of Classification Rules from Partially Classified Data. CoRR Geoffrey J. McLachlan, Daniel Ahfock
2020	J	`jnl`	Mini-batch learning of exponential family finite mixture models. Stat. Comput. Hien Duy Nguyen, Florence Forbes, Geoffrey J. McLachlan
2019	J	`jnl`	Deep Gaussian mixture models. Stat. Comput. Cinzia Viroli, Geoffrey J. McLachlan
2019	J	`jnl`	PPEM: Privacy-preserving EM learning for mixture models. Concurr. Comput. Pract. Exp. Sharon X. Lee, Kaleb L. Leemaqz, Geoffrey J. McLachlan
2019	J	`jnl`	Unsupervised pattern recognition of mixed data structures with numerical and categorical features using a mixture regression modelling framework. Pattern Recognit. Shu-Kay Ng, Richard Tawiah, Geoffrey J. McLachlan
2018	J	`jnl`	A Block EM Algorithm for Multivariate Skew Normal and Skew $t$ -Mixture Models. IEEE Trans. Neural Networks Learn. Syst. Sharon X. Lee, Kaleb L. Leemaqz, Geoffrey J. McLachlan
2018	J	`jnl`	A globally convergent algorithm for lasso-penalized mixture of linear regression models. Comput. Stat. Data Anal. Luke R. Lloyd-Jones, Hien Duy Nguyen, Geoffrey J. McLachlan
2018	Misc	`conf`	Positive Data Kernel Density Estimation via the LogKDE Package for R. AusDM Hien D. Nguyen, Andrew T. Jones, Geoffrey J. McLachlan
2018	J	`jnl`	Randomized mixture models for probability density approximation and estimation. Inf. Sci. Hien Duy Nguyen, Dianhui Wang, Geoffrey J. McLachlan
2018	J	`jnl`	Whole-volume clustering of time series data from zebrafish brain calcium images via mixture modeling. Stat. Anal. Data Min. Hien Duy Nguyen, Jeremy F. P. Ullmann, Geoffrey J. McLachlan, Venkatakaushik Voleti, Wenze Li, Elizabeth M. C. Hillman, David C. Reutens, Andrew L. Janke
2018	J	`jnl`	logKDE: log-transformed kernel density estimation. J. Open Source Softw. Andrew T. Jones, Hien Duy Nguyen, Geoffrey J. McLachlan
2017	—	`conf`	Corruption-Resistant Privacy Preserving Distributed EM Algorithm for Model-Based Clustering. TrustCom/BigDataSE/ICESS Kaleb L. Leemaqz, Sharon X. Lee, Geoffrey J. McLachlan
2017	J	`jnl`	Deep Gaussian Mixture Models. CoRR Cinzia Viroli, Geoffrey J. McLachlan
2017	J	`jnl`	Iteratively-Reweighted Least-Squares Fitting of Support Vector Machines: A Majorization-Minimization Algorithm Approach. CoRR Hien D. Nguyen, Geoffrey J. McLachlan
2017	J	`jnl`	Maximum Pseudolikelihood Estimation for Model-Based Clustering of Time Series Data. Neural Comput. Hien Duy Nguyen, Geoffrey J. McLachlan, Pierre Orban, Pierre Bellec, Andrew L. Janke
2017	—	`conf`	Private Distributed Three-Party Learning of Gaussian Mixture Models. ATIS Kaleb L. Leemaqz, Sharon X. Lee, Geoffrey J. McLachlan
2016	J	`jnl`	A Block Minorization-Maximization Algorithm for Heteroscedastic Regression. IEEE Signal Process. Lett. Hien Duy Nguyen, Luke R. Lloyd-Jones, Geoffrey J. McLachlan
2016	Misc	`conf`	A Simple Parallel EM Algorithm for Statistical Learning via Mixture Models. DICTA Sharon X. Lee, Kaleb L. Leemaqz, Geoffrey J. McLachlan
2016	J	`jnl`	A Universal Approximation Theorem for Mixture-of-Experts Models. Neural Comput. Hien Duy Nguyen, Luke R. Lloyd-Jones, Geoffrey J. McLachlan
2016	J	`jnl`	A block EM algorithm for multivariate skew normal and skew t-mixture models. CoRR Sharon X. Lee, Kaleb L. Leemaqz, Geoffrey J. McLachlan
2016	J	`jnl`	Extending mixtures of factor models using the restricted multivariate skew-normal distribution. J. Multivar. Anal. Tsung-I Lin, Geoffrey J. McLachlan, Sharon X. Lee
2016	—	`conf`	Finding group structures in "Big Data" in healthcare research using mixture models. BIBM Shu-Kay Ng, Geoffrey J. McLachlan
2016	J	`jnl`	Finite mixtures of canonical fundamental skew t-distributions - The unification of the restricted and unrestricted skew t-mixture models. Stat. Comput. Sharon X. Lee, Geoffrey J. McLachlan
2016	J	`jnl`	Laplace mixture of linear experts. Comput. Stat. Data Anal. Hien Duy Nguyen, Geoffrey J. McLachlan
2016	J	`jnl`	Linear mixed models with marginally symmetric nonparametric random effects. Comput. Stat. Data Anal. Hien Duy Nguyen, Geoffrey J. McLachlan
2016	J	`jnl`	Maximum likelihood estimation of triangular and polygonal distributions. Comput. Stat. Data Anal. Hien Duy Nguyen, Geoffrey J. McLachlan
2016	J	`jnl`	Mixtures of spatial spline regressions for clustering and classification. Comput. Stat. Data Anal. Hien Duy Nguyen, Geoffrey J. McLachlan, Ian A. Wood
2016	J	`jnl`	Partial identification in the statistical matching problem. Comput. Stat. Data Anal. Daniel Ahfock, Saumyadipta Pyne, Sharon X. Lee, Geoffrey J. McLachlan
2016	C	`conf`	Unsupervised Component-Wise EM Learning for Finite Mixtures of Skew t-distributions. ADMA Sharon X. Lee, Geoffrey J. McLachlan
2015	J	`jnl`	Maximum likelihood estimation of Gaussian mixture models without matrix operations. Adv. Data Anal. Classif. Hien Duy Nguyen, Geoffrey J. McLachlan
2014	—	`conf`	Asymptotic inference for hidden process regression models. SSP Hien Duy Nguyen, Geoffrey J. McLachlan
2014	J	`jnl`	False Discovery Rate Control in Magnetic Resonance Imaging Studies via Markov Random Fields. IEEE Trans. Medical Imaging Hien Duy Nguyen, Geoffrey J. McLachlan, Nicolas Cherbuin, Andrew L. Janke
2014	J	`jnl`	Finite mixtures of multivariate skew t-distributions: some recent and new results. Stat. Comput. Sharon X. Lee, Geoffrey J. McLachlan
2014	J	`jnl`	Mixture models for clustering multilevel growth trajectories. Comput. Stat. Data Anal. Shu-Kay Ng, Geoffrey J. McLachlan
2014	J	`jnl`	On the number of components in a Gaussian mixture model. WIREs Data Mining Knowl. Discov. Geoffrey J. McLachlan, Suren I. Rathnayake
2014	J	`jnl`	The 2nd special issue on advances in mixture models. Comput. Stat. Data Anal. Dankmar Böhning, Christian Hennig, Geoffrey J. McLachlan, Paul D. McNicholas
2013	—	`ed.`	2013 IEEE International Conference on Bioinformatics and Biomedicine, Shanghai, China, December 18-21, 2013 BIBM Guo-Zheng Li, Sunghoon Kim, Michael Hughes, Geoffrey J. McLachlan, Hongye Sun, Xiaohua Hu, Habtom W. Ressom, Baoyan Liu, Michael N. Liebman
2013	—	`conf`	A common factor-analytic model for classification. BIBM Mingzhu Sun, Geoffrey J. McLachlan
2013	J	`jnl`	Model-based clustering and classification with non-normal mixture distributions. Stat. Methods Appl. Sharon X. Lee, Geoffrey J. McLachlan
2013	J	`jnl`	On mixtures of skew normal and skew t-distributions. Adv. Data Anal. Classif. Sharon X. Lee, Geoffrey J. McLachlan
2013	J	`jnl`	On the classification of microarray gene-expression data. Briefings Bioinform. Kaye E. Basford, Geoffrey J. McLachlan, Suren I. Rathnayake
2013	J	`jnl`	Rejoinder to the discussion of "Model-based clustering and classification with non-normal mixture distributions". Stat. Methods Appl. Sharon X. Lee, Geoffrey J. McLachlan
2013	Misc	`conf`	Spatial False Discovery Rate Control for Magnetic Resonance Imaging Studies. DICTA Hien Duy Nguyen, Andrew L. Janke, Nicolas Cherbuin, Geoffrey J. McLachlan, Perminder S. Sachdev, Kaarin Anstey
2013	—	`conf`	Using cluster analysis to improve gene selection in the formation of discriminant rules for the prediction of disease outcomes. BIBM Shu-Kay Ng, Geoffrey J. McLachlan
2012	—	`ch.`	An Enduring Interest in Classification: Supervised and Unsupervised. Journeys to Data Mining Geoffrey J. McLachlan
2012	J	`jnl`	Clustering of time-course gene expression profiles using normal mixture models with autoregressive random effects. BMC Bioinform. Kui Wang, Shu-Kay Ng, Geoffrey J. McLachlan
2012	J	`jnl`	Top-10 Data Mining Case Studies. Int. J. Inf. Technol. Decis. Mak. 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
2011	J	`jnl`	Classification of High-Dimensional microarray Data with a Two-Step Procedure via a Wilcoxon Criterion and Multilayer Perceptron. Int. J. Comput. Intell. Appl. Vladimir Nikulin, Tian-Hsiang Huang, Geoffrey J. McLachlan
2011	J	`jnl`	Mixtures of common Bioinform. Jangsun Baek, Geoffrey J. McLachlan
2010	J	`jnl`	A Very Fast Algorithm for Matrix Factorization CoRR Vladimir Nikulin, Tian-Hsiang Huang, Shu-Kay Ng, Suren I. Rathnayake, Geoffrey J. McLachlan
2010	—	`conf`	A comparative study of two matrix factorization methods applied to the classification of gene expression data. BIBM Vladimir Nikulin, Tian-Hsiang Huang, Geoffrey J. McLachlan
2010	A*	`conf`	Assessing the Significance of Groups in High-Dimensional Data. ICDM Geoffrey J. McLachlan
2010	B	`conf`	Automated High-Dimensional Flow Cytometric Data Analysis. RECOMB 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
2010	B	`conf`	Identifying fiber bundles with regularised к-means clustering applied to the grid-based data. IJCNN Vladimir Nikulin, Geoffrey J. McLachlan
2010	J	`jnl`	Integrative mixture of experts to combine clinical factors and gene markers. Bioinform. Kim-Anh Lê Cao, Emmanuelle Meugnier, Geoffrey J. McLachlan
2010	J	`jnl`	Mixtures of Factor Analyzers with Common Factor Loadings: Applications to the Clustering and Visualization of High-Dimensional Data. IEEE Trans. Pattern Anal. Mach. Intell. Jangsun Baek, Geoffrey J. McLachlan, Lloyd K. Flack
2010	—	`conf`	On the Gradient-based Algorithm for Matrix Factorization Applied to Dimensionality Reduction. BIOINFORMATICS Vladimir Nikulin, Geoffrey J. McLachlan
2009	—	`conf`	Classification of Imbalanced Marketing Data with Balanced Random Sets. KDD Cup Vladimir Nikulin, Geoffrey J. McLachlan
2009	—	`conf`	Ensemble Approach for the Classification of Imbalanced Data. Australasian Conference on Artificial Intelligence Vladimir Nikulin, Geoffrey J. McLachlan, Shu-Kay Ng
2009	Misc	`conf`	Multivariate Skew t Mixture Models: Applications to Fluorescence-Activated Cell Sorting Data. DICTA Kui Wang, Shu-Kay Ng, Geoffrey J. McLachlan
2009	—	`conf`	Penalized Principal Component Analysis of Microarray Data. CIBB Vladimir Nikulin, Geoffrey J. McLachlan
2008	—	`conf`	Clustering of High-Dimensional Data via Finite Mixture Models. GfKl Geoffrey J. McLachlan, Jangsun Baek
2008	J	`jnl`	Top 10 algorithms in data mining. Knowl. Inf. Syst. 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
2008	J	`jnl`	Wallace's Approach to Unsupervised Learning: The Snob Program. Comput. J. Murray A. Jorgensen, Geoffrey J. McLachlan
2007	J	`jnl`	Extension of mixture-of-experts networks for binary classification of hierarchical data. Artif. Intell. Medicine Shu-Kay Ng, Geoffrey J. McLachlan
2007	J	`jnl`	Extension of the mixture of factor analyzers model to incorporate the multivariate t-distribution. Comput. Stat. Data Anal. Geoffrey J. McLachlan, Richard W. Bean, Liat Ben-Tovim Jones
2007	—	`conf`	Merging Algorithm to Reduce Dimensionality in Application to Web-Mining. Australian Conference on Artificial Intelligence Vladimir Nikulin, Geoffrey J. McLachlan
2007	J	`jnl`	Multilevel survival modelling of recurrent urinary tract infections. Comput. Methods Programs Biomed. Kui Wang, Kelvin K. W. Yau, Andy H. Lee, Geoffrey J. McLachlan
2007	J	`jnl`	Segmentation and intensity estimation of microarray images using a gamma-t mixture model. Bioinform. Jangsun Baek, Young Sook Son, Geoffrey J. McLachlan
2007	J	`jnl`	Two-component Poisson mixture regression modelling of count data with bivariate random effects. Math. Comput. Model. Kui Wang, Kelvin K. W. Yau, Andy H. Lee, Geoffrey J. McLachlan
2006	J	`jnl`	A Mixture model with random-effects components for clustering correlated gene-expression profiles. Bioinform. Shu-Kay Ng, Geoffrey J. McLachlan, Kui Wang, Liat Ben-Tovim Jones, S.-W. Ng
2006	J	`jnl`	A simple implementation of a normal mixture approach to differential gene expression in multiclass microarrays. Bioinform. Geoffrey J. McLachlan, Richard W. Bean, Liat Ben-Tovim Jones
2006	J	`jnl`	An incremental EM-based learning approach for on-line prediction of hospital resource utilization. Artif. Intell. Medicine Shu-Kay Ng, Geoffrey J. McLachlan, Andy H. Lee
2006	J	`jnl`	Mixture Models for Detecting Differentially Expressed Genes in Microarrays. Int. J. Neural Syst. Liat Ben-Tovim Jones, Richard Bean, Geoffrey J. McLachlan, Justin Xi Zhu
2005	C	`conf`	Application of Mixture Models to Detect Differentially Expressed Genes. IDEAL Liat Ben-Tovim Jones, Richard Bean, Geoffrey J. McLachlan, Justin Xi Zhu
2005	C	`conf`	Cluster Analysis of High-Dimensional Data: A Case Study. IDEAL Richard Bean, Geoffrey J. McLachlan
2005	—	`conf`	Normalized Gaussian Networks with Mixed Feature Data. Australian Conference on Artificial Intelligence Shu-Kay Ng, Geoffrey J. McLachlan
2004	B	`conf`	On the Simultaneous Use of Clinical and Microarray Expression Data in the Cluster Analysis of Tissue Samples. APBC Geoffrey J. McLachlan, Soong Chang, Jess Mar, Christophe Ambroise, Justin Xi Zhu
2004	J	`jnl`	Speeding up the EM algorithm for mixture model-based segmentation of magnetic resonance images. Pattern Recognit. Shu-Kay Ng, Geoffrey J. McLachlan
2004	J	`jnl`	Using the EM algorithm to train neural networks: misconceptions and a new algorithm for multiclass classification. IEEE Trans. Neural Networks Shu-Kay Ng, Geoffrey J. McLachlan
2003	J	`jnl`	Model-Based Clustering In Gene Expression Microarrays: An Application To Breast Cancer Data. Int. J. Softw. Eng. Knowl. Eng. J. C. Mar, Geoffrey J. McLachlan
2003	B	`conf`	Model-Based Clustering in Gene Expression Microarrays: An Application to Breast Cancer Data. APBC J. C. Mar, Geoffrey J. McLachlan
2003	J	`jnl`	Modelling high-dimensional data by mixtures of factor analyzers. Comput. Stat. Data Anal. Geoffrey J. McLachlan, David Peel, Richard W. Bean
2003	J	`jnl`	On the choice of the number of blocks with the incremental EM algorithm for the fitting of normal mixtures. Stat. Comput. Shu-Kay Ng, Geoffrey J. McLachlan
2003	Misc	`conf`	Robust Estimation in Gaussian Mixtures Using Multiresolution Kd-trees. DICTA Shu-Kay Ng, Geoffrey J. McLachlan
2002	J	`jnl`	A mixture model-based approach to the clustering of microarray expression data. Bioinform. Geoffrey J. McLachlan, Richard W. Bean, David Peel
2002	J	`jnl`	Maximum Likelihood Estimation of Mixture Densities for Binned and Truncated Multivariate Data. Mach. Learn. Igor V. Cadez, Padhraic Smyth, Geoffrey J. McLachlan, Christine E. McLaren
2000	—	`book`	Finite Mixture Models Geoffrey J. McLachlan, David Peel
2000	A*	`conf`	Mixtures of Factor Analyzers. ICML Geoffrey J. McLachlan, David Peel
2000	J	`jnl`	Robust mixture modelling using the t distribution. Stat. Comput. David Peel, Geoffrey J. McLachlan
1999	A*	`conf`	Hierarchical Models for Screening of Iron Deficiency Anemia. ICML Igor V. Cadez, Christine E. McLaren, Padhraic Smyth, Geoffrey J. McLachlan
1998	B	`conf`	MIXFIT: an algorithm for the automatic fitting and testing of normal mixture models. ICPR Geoffrey J. McLachlan, David Peel
1998	A*	`conf`	Mining in the Presence of Selectivity Bias and its Application to Reject Inference. KDD A. J. Feelders, Soong Chang, Geoffrey J. McLachlan
1998	—	`conf`	Robust Cluster Analysis via Mixtures of Multivariate t-Distributions. SSPR/SPR Geoffrey J. McLachlan, David Peel
1996	J	`jnl`	Maximum likelihood clustering via normal mixture models. Signal Process. Image Commun. Geoffrey J. McLachlan, David Peel, W. J. Whiten
1989	J	`jnl`	Bias associated with the discriminant analysis approach to the estimation of mixing proportions. Pattern Recognit. Charles R. O. Lawoko, Geoffrey J. McLachlan
1988	J	`jnl`	Further results on discrimination with autocorrelated observations. Pattern Recognit. Charles R. O. Lawoko, Geoffrey J. McLachlan
1986	J	`jnl`	Asymptotic error rates of the W and Z statistics when the training observations are dependent. Pattern Recognit. Charles R. O. Lawoko, Geoffrey J. McLachlan
1985	J	`jnl`	Discrimination with autocorrelated observations. Pattern Recognit. Charles R. O. Lawoko, Geoffrey J. McLachlan
1983	J	`jnl`	Some asymptotic results on the effect of autocorrelation on the error rates of the sample linear discriminant function. Pattern Recognit. Charles R. O. Lawoko, Geoffrey J. McLachlan
1982	—	`ch.`	9 The classification and mixture maximum likelihood approaches to cluster analysis. Classification, Pattern Recognition and Reduction of Dimensionality Geoffrey J. McLachlan
1980	J	`jnl`	Error rate estimation on the basis of posterior probabilities. Pattern Recognit. S. Ganesalingam, Geoffrey J. McLachlan
1977	J	`jnl`	A note on the choice of a weighting function to give an efficient method for estimating the probability of misclassification. Pattern Recognit. Geoffrey J. McLachlan
1976	J	`jnl`	Further results on the effect of intraclass correlation among training samples in discriminant analysis. Pattern Recognit. Geoffrey J. McLachlan