Clustering with Bregman Divergences
The Journal of Machine Learning Research
A Nonlinear Mapping for Data Structure Analysis
IEEE Transactions on Computers
Nonlinear Dimensionality Reduction
Nonlinear Dimensionality Reduction
Curvilinear component analysis: a self-organizing neural network for nonlinear mapping of data sets
IEEE Transactions on Neural Networks
Extending metric multidimensional scaling with Bregman divergences
Pattern Recognition
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We investigate multidimensional scaling with Bregman divergences and show that the Sammon mapping can be thought of as a truncated Bregman multidimensional scaling (BMDS). We show that the full BMDS improves upon the Sammon mapping on some standard data sets and investigate the reasons underlying this improvement. We then introduce two families of BMDS which use opposite strategies to create good mappings of standard data sets and investigate these opposite strategies analytically.