According to our database1, Shu-Kay Ng authored at least 18 papers between 2003 and 2019.
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Unsupervised pattern recognition of mixed data structures with numerical and categorical features using a mixture regression modelling framework.
Pattern Recognition, 2019
Finding group structures in "Big Data" in healthcare research using mixture models.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2016
Mixture models for clustering multilevel growth trajectories.
Computational Statistics & Data Analysis, 2014
Automatic Segmentation of Molecular Pathology Images Using a Robust Mixture Model with Markov Random Fields.
Proceedings of the 2013 International Conference on Digital Image Computing: Techniques and Applications, 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
Clustering of time-course gene expression profiles using normal mixture models with autoregressive random effects.
BMC Bioinformatics, 2012
A Very Fast Algorithm for Matrix Factorization
A computer graphical user interface for survival mixture modelling of recurrent infections.
Comp. in Bio. and Med., 2009
Multivariate Skew t Mixture Models: Applications to Fluorescence-Activated Cell Sorting Data.
Proceedings of the DICTA 2009, 2009
Ensemble Approach for the Classification of Imbalanced Data.
Proceedings of the AI 2009: Advances in Artificial Intelligence, 2009
Extension of mixture-of-experts networks for binary classification of hierarchical data.
Artificial Intelligence in Medicine, 2007
A Mixture model with random-effects components for clustering correlated gene-expression profiles.
An incremental EM-based learning approach for on-line prediction of hospital resource utilization.
Artificial Intelligence in Medicine, 2006
Normalized Gaussian Networks with Mixed Feature Data.
Proceedings of the AI 2005: Advances in Artificial Intelligence, 2005
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 choice of the number of blocks with the incremental EM algorithm for the fitting of normal mixtures.
Statistics and Computing, 2003
Robust Estimation in Gaussian Mixtures Using Multiresolution Kd-trees.
Proceedings of the Seventh International Conference on Digital Image Computing: Techniques and Applications, 2003