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KDD
2004
ACM
187views Data Mining» more  KDD 2004»
15 years 10 months ago
IMMC: incremental maximum margin criterion
Subspace learning approaches have attracted much attention in academia recently. However, the classical batch algorithms no longer satisfy the applications on streaming data or la...
Jun Yan, Benyu Zhang, Shuicheng Yan, Qiang Yang, H...
KDD
2007
ACM
124views Data Mining» more  KDD 2007»
15 years 4 months ago
Hierarchical mixture models: a probabilistic analysis
Mixture models form one of the most widely used classes of generative models for describing structured and clustered data. In this paper we develop a new approach for the analysis...
Mark Sandler
FCSC
2010
238views more  FCSC 2010»
14 years 7 months ago
Knowledge discovery through directed probabilistic topic models: a survey
Graphical models have become the basic framework for topic based probabilistic modeling. Especially models with latent variables have proved to be effective in capturing hidden str...
Ali Daud, Juanzi Li, Lizhu Zhou, Faqir Muhammad
IJCNN
2007
IEEE
15 years 4 months ago
The Metro Visualisation of Component Planes for Self-Organising Maps
— The Self-Organising Map is a popular unsupervised neural network model which has successfully been used for clustering various kinds of data. To help in understanding the infl...
Robert Neumayer, Rudolf Mayer, Georg Pölzlbau...
ISNN
2005
Springer
15 years 3 months ago
An Improvement on PCA Algorithm for Face Recognition
Principle Component Analysis (PCA) technique is an important and well-developed area of image recognition and to date many linear discrimination methods have been put forward. Desp...
Vo Dinh Minh Nhat, Sungyoung Lee