Geoffrey J. McLachlan

According to our database1, Geoffrey J. McLachlan authored at least 99 papers between 1976 and 2019.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2019
Deep Gaussian mixture models.
Statistics and Computing, 2019

Unsupervised pattern recognition of mixed data structures with numerical and categorical features using a mixture regression modelling framework.
Pattern Recognition, 2019

2018
A Block EM Algorithm for Multivariate Skew Normal and Skew $t$ -Mixture Models.
IEEE Trans. Neural Netw. Learning Syst., 2018

Whole-volume clustering of time series data from zebrafish brain calcium images via mixture modeling.
Statistical Analysis and Data Mining, 2018

logKDE: log-transformed kernel density estimation.
J. Open Source Software, 2018

Randomized mixture models for probability density approximation and estimation.
Inf. Sci., 2018

A globally convergent algorithm for lasso-penalized mixture of linear regression models.
Computational Statistics & Data Analysis, 2018

Positive Data Kernel Density Estimation via the LogKDE Package for R.
Proceedings of the Data Mining - 16th Australasian Conference, AusDM 2018, Bahrurst, NSW, 2018

2017
Maximum Pseudolikelihood Estimation for Model-Based Clustering of Time Series Data.
Neural Computation, 2017

Deep Gaussian Mixture Models.
CoRR, 2017

Iteratively-Reweighted Least-Squares Fitting of Support Vector Machines: A Majorization-Minimization Algorithm Approach.
CoRR, 2017

Corruption-Resistant Privacy Preserving Distributed EM Algorithm for Model-Based Clustering.
Proceedings of the 2017 IEEE Trustcom/BigDataSE/ICESS, Sydney, Australia, August 1-4, 2017, 2017

Private Distributed Three-Party Learning of Gaussian Mixture Models.
Proceedings of the Applications and Techniques in Information Security, 2017

2016
A Block Minorization-Maximization Algorithm for Heteroscedastic Regression.
IEEE Signal Process. Lett., 2016

Finite mixtures of canonical fundamental skew t-distributions - The unification of the restricted and unrestricted skew t-mixture models.
Statistics and Computing, 2016

A Universal Approximation Theorem for Mixture-of-Experts Models.
Neural Computation, 2016

Extending mixtures of factor models using the restricted multivariate skew-normal distribution.
J. Multivariate Analysis, 2016

Mixtures of spatial spline regressions for clustering and classification.
Computational Statistics & Data Analysis, 2016

Linear mixed models with marginally symmetric nonparametric random effects.
Computational Statistics & Data Analysis, 2016

Maximum likelihood estimation of triangular and polygonal distributions.
Computational Statistics & Data Analysis, 2016

Laplace mixture of linear experts.
Computational Statistics & Data Analysis, 2016

Partial identification in the statistical matching problem.
Computational Statistics & Data Analysis, 2016

A block EM algorithm for multivariate skew normal and skew t-mixture models.
CoRR, 2016

A Simple Parallel EM Algorithm for Statistical Learning via Mixture Models.
Proceedings of the 2016 International Conference on Digital Image Computing: Techniques and Applications, 2016

Finding group structures in "Big Data" in healthcare research using mixture models.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2016

Unsupervised Component-Wise EM Learning for Finite Mixtures of Skew t-distributions.
Proceedings of the Advanced Data Mining and Applications - 12th International Conference, 2016

2015
Maximum likelihood estimation of Gaussian mixture models without matrix operations.
Adv. Data Analysis and Classification, 2015

2014
On the number of components in a Gaussian mixture model.
Wiley Interdiscip. Rev. Data Min. Knowl. Discov., 2014

False Discovery Rate Control in Magnetic Resonance Imaging Studies via Markov Random Fields.
IEEE Trans. Med. Imaging, 2014

Finite mixtures of multivariate skew t-distributions: some recent and new results.
Statistics and Computing, 2014

Mixture models for clustering multilevel growth trajectories.
Computational Statistics & Data Analysis, 2014

The 2nd special issue on advances in mixture models.
Computational Statistics & Data Analysis, 2014

Asymptotic inference for hidden process regression models.
Proceedings of the IEEE Workshop on Statistical Signal Processing, 2014

2013
Rejoinder to the discussion of "Model-based clustering and classification with non-normal mixture distributions".
Statistical Methods and Applications, 2013

Model-based clustering and classification with non-normal mixture distributions.
Statistical Methods and Applications, 2013

On the classification of microarray gene-expression data.
Briefings in Bioinformatics, 2013

On mixtures of skew normal and skew t-distributions.
Adv. Data Analysis and Classification, 2013

Spatial False Discovery Rate Control for Magnetic Resonance Imaging Studies.
Proceedings of the 2013 International Conference on Digital Image Computing: Techniques and Applications, 2013

A common factor-analytic model for classification.
Proceedings of the 2013 IEEE International Conference on Bioinformatics and Biomedicine, 2013

Using cluster analysis to improve gene selection in the formation of discriminant rules for the prediction of disease outcomes.
Proceedings of the 2013 IEEE International Conference on Bioinformatics and Biomedicine, 2013

2012
Top-10 Data Mining Case Studies.
International Journal of Information Technology and Decision Making, 2012

Clustering of time-course gene expression profiles using normal mixture models with autoregressive random effects.
BMC Bioinformatics, 2012

An Enduring Interest in Classification: Supervised and Unsupervised.
Proceedings of the Journeys to Data Mining, 2012

2011
Classification of High-Dimensional microarray Data with a Two-Step Procedure via a Wilcoxon Criterion and Multilayer Perceptron.
International Journal of Computational Intelligence and Applications, 2011

Mixtures of common t-factor analyzers for clustering high-dimensional microarray data.
Bioinformatics, 2011

2010
Mixtures of Factor Analyzers with Common Factor Loadings: Applications to the Clustering and Visualization of High-Dimensional Data.
IEEE Trans. Pattern Anal. Mach. Intell., 2010

A Very Fast Algorithm for Matrix Factorization
CoRR, 2010

Integrative mixture of experts to combine clinical factors and gene markers.
Bioinformatics, 2010

Automated High-Dimensional Flow Cytometric Data Analysis.
Proceedings of the Research in Computational Molecular Biology, 2010

Identifying fiber bundles with regularised к-means clustering applied to the grid-based data.
Proceedings of the International Joint Conference on Neural Networks, 2010

Assessing the Significance of Groups in High-Dimensional Data.
Proceedings of the ICDM 2010, 2010

On the Gradient-based Algorithm for Matrix Factorization Applied to Dimensionality Reduction.
Proceedings of the BIOINFORMATICS 2010, 2010

A comparative study of two matrix factorization methods applied to the classification of gene expression data.
Proceedings of the 2010 IEEE International Conference on Bioinformatics and Biomedicine, 2010

2009
Classification of Imbalanced Marketing Data with Balanced Random Sets.
Proceedings of KDD-Cup 2009 competition, Paris, France, June 28, 2009, 2009

Multivariate Skew t Mixture Models: Applications to Fluorescence-Activated Cell Sorting Data.
Proceedings of the DICTA 2009, 2009

Penalized Principal Component Analysis of Microarray Data.
Proceedings of the Computational Intelligence Methods for Bioinformatics and Biostatistics, 2009

Ensemble Approach for the Classification of Imbalanced Data.
Proceedings of the AI 2009: Advances in Artificial Intelligence, 2009

2008
Top 10 algorithms in data mining.
Knowl. Inf. Syst., 2008

Wallace's Approach to Unsupervised Learning: The Snob Program.
Comput. J., 2008

Clustering of High-Dimensional Data via Finite Mixture Models.
Proceedings of the Advances in Data Analysis, Data Handling and Business Intelligence, 2008

2007
Two-component Poisson mixture regression modelling of count data with bivariate random effects.
Mathematical and Computer Modelling, 2007

Extension of the mixture of factor analyzers model to incorporate the multivariate t-distribution.
Computational Statistics & Data Analysis, 2007

Multilevel survival modelling of recurrent urinary tract infections.
Computer Methods and Programs in Biomedicine, 2007

Segmentation and intensity estimation of microarray images using a gamma-t mixture model.
Bioinformatics, 2007

Extension of mixture-of-experts networks for binary classification of hierarchical data.
Artificial Intelligence in Medicine, 2007

Merging Algorithm to Reduce Dimensionality in Application to Web-Mining.
Proceedings of the AI 2007: Advances in Artificial Intelligence, 2007

2006
Mixture Models for Detecting Differentially Expressed Genes in Microarrays.
Int. J. Neural Syst., 2006

A Mixture model with random-effects components for clustering correlated gene-expression profiles.
Bioinformatics, 2006

A simple implementation of a normal mixture approach to differential gene expression in multiclass microarrays.
Bioinformatics, 2006

An incremental EM-based learning approach for on-line prediction of hospital resource utilization.
Artificial Intelligence in Medicine, 2006

2005
Application of Mixture Models to Detect Differentially Expressed Genes.
Proceedings of the Intelligent Data Engineering and Automated Learning, 2005

Cluster Analysis of High-Dimensional Data: A Case Study.
Proceedings of the Intelligent Data Engineering and Automated Learning, 2005

Normalized Gaussian Networks with Mixed Feature Data.
Proceedings of the AI 2005: Advances in Artificial Intelligence, 2005

2004
Using the EM algorithm to train neural networks: misconceptions and a new algorithm for multiclass classification.
IEEE Trans. Neural Networks, 2004

Speeding up the EM algorithm for mixture model-based segmentation of magnetic resonance images.
Pattern Recognition, 2004

On the Simultaneous Use of Clinical and Microarray Expression Data in the Cluster Analysis of Tissue Samples.
Proceedings of the Second Asia-Pacific Bioinformatics Conference (APBC 2004), 2004

2003
On the choice of the number of blocks with the incremental EM algorithm for the fitting of normal mixtures.
Statistics and Computing, 2003

Model-Based Clustering In Gene Expression Microarrays: An Application To Breast Cancer Data.
International Journal of Software Engineering and Knowledge Engineering, 2003

Modelling high-dimensional data by mixtures of factor analyzers.
Computational Statistics & Data Analysis, 2003

Robust Estimation in Gaussian Mixtures Using Multiresolution Kd-trees.
Proceedings of the Seventh International Conference on Digital Image Computing: Techniques and Applications, 2003

Model-Based Clustering in Gene Expression Microarrays: An Application to Breast Cancer Data.
Proceedings of the First Asia-Pacific Bioinformatics Conference (APBC 2003), 2003

2002
Maximum Likelihood Estimation of Mixture Densities for Binned and Truncated Multivariate Data.
Machine Learning, 2002

A mixture model-based approach to the clustering of microarray expression data.
Bioinformatics, 2002

2000
Robust mixture modelling using the t distribution.
Statistics and Computing, 2000

Mixtures of Factor Analyzers.
Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000

Finite Mixture Models
Wiley Series in Probability and Statistics, Wiley, ISBN: 978-0-47172118-5, 2000

1999
Hierarchical Models for Screening of Iron Deficiency Anemia.
Proceedings of the Sixteenth International Conference on Machine Learning (ICML 1999), Bled, Slovenia, June 27, 1999

1998
Robust Cluster Analysis via Mixtures of Multivariate t-Distributions.
Proceedings of the Advances in Pattern Recognition, 1998

Mining in the Presence of Selectivity Bias and its Application to Reject Inference.
Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining (KDD-98), 1998

MIXFIT: an algorithm for the automatic fitting and testing of normal mixture models.
Proceedings of the Fourteenth International Conference on Pattern Recognition, 1998

1996
Maximum likelihood clustering via normal mixture models.
Sig. Proc.: Image Comm., 1996

1989
Bias associated with the discriminant analysis approach to the estimation of mixing proportions.
Pattern Recognition, 1989

1988
Further results on discrimination with autocorrelated observations.
Pattern Recognition, 1988

1986
Asymptotic error rates of the W and Z statistics when the training observations are dependent.
Pattern Recognition, 1986

1985
Discrimination with autocorrelated observations.
Pattern Recognition, 1985

1983
Some asymptotic results on the effect of autocorrelation on the error rates of the sample linear discriminant function.
Pattern Recognition, 1983

1980
Error rate estimation on the basis of posterior probabilities.
Pattern Recognition, 1980

1977
A note on the choice of a weighting function to give an efficient method for estimating the probability of misclassification.
Pattern Recognition, 1977

1976
Further results on the effect of intraclass correlation among training samples in discriminant analysis.
Pattern Recognition, 1976


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