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2020 – today
- 2023
[j11]Xuewei Cheng
, Sizheng Wang, Hong Wang, Shu-Kay Ng:
Deep survival forests for extremely high censored data. Appl. Intell. 53(6): 7041-7055 (2023)- 2022
- [c8]A Hasitha Kuruwita, Shu-Kay Ng, Alan Wee-Chung Liew, Brent Richards, Kelvin Ross, Kuldeep Kumar, Luke Haseler, Meghan McConnell, Ping Zhang:
Ectopic Heartbeat Detection from ECG Signals using Deep Convolutional Neural Networks. BIBM 2022: 3535-3540
2010 – 2019
- 2019
- [j10]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: 261-271 (2019) - 2016
- [c7]Shu-Kay Ng, Geoffrey J. McLachlan:
Finding group structures in "Big Data" in healthcare research using mixture models. BIBM 2016: 1214-1219 - 2014
- [j9]Shu-Kay Ng, Geoffrey J. McLachlan:
Mixture models for clustering multilevel growth trajectories. Comput. Stat. Data Anal. 71: 43-51 (2014) - 2013
- [c6]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: 267-272 - [c5]Shu-Kay Ng, Alfred K. Lam:
Automatic Segmentation of Molecular Pathology Images Using a Robust Mixture Model with Markov Random Fields. DICTA 2013: 1-8 - 2012
- [j8]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: 300 (2012) - 2010
- [i1]Vladimir Nikulin, Tian-Hsiang Huang, Shu-Kay Ng, Suren I. Rathnayake, Geoffrey J. McLachlan:
A Very Fast Algorithm for Matrix Factorization. CoRR abs/1011.0506 (2010)
2000 – 2009
- 2009
- [j7]Andy H. Lee, Yun Zhao, Kelvin K. W. Yau, Shu-Kay Ng:
A computer graphical user interface for survival mixture modelling of recurrent infections. Comput. Biol. Medicine 39(3): 301-307 (2009) - [c4]Vladimir Nikulin, Geoffrey J. McLachlan, Shu-Kay Ng:
Ensemble Approach for the Classification of Imbalanced Data. Australasian Conference on Artificial Intelligence 2009: 291-300 - [c3]Kui Wang, Shu-Kay Ng, Geoffrey J. McLachlan:
Multivariate Skew t Mixture Models: Applications to Fluorescence-Activated Cell Sorting Data. DICTA 2009: 526-531 - 2007
- [j6]Shu-Kay Ng, Geoffrey J. McLachlan:
Extension of mixture-of-experts networks for binary classification of hierarchical data. Artif. Intell. Medicine 41(1): 57-67 (2007) - 2006
- [j5]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): 257-267 (2006) - [j4]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): 1745-1752 (2006) - 2005
- [c2]Shu-Kay Ng, Geoffrey J. McLachlan:
Normalized Gaussian Networks with Mixed Feature Data. Australian Conference on Artificial Intelligence 2005: 879-882 - 2004
- [j3]Shu-Kay Ng, Geoffrey J. McLachlan:
Speeding up the EM algorithm for mixture model-based segmentation of magnetic resonance images. Pattern Recognit. 37(8): 1573-1589 (2004) - [j2]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): 738-749 (2004) - 2003
- [j1]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): 45-55 (2003) - [c1]Shu-Kay Ng, Geoffrey J. McLachlan:
Robust Estimation in Gaussian Mixtures Using Multiresolution Kd-trees. DICTA 2003: 145-154
Coauthor Index
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