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xSNE Stochastic Neighbor Embedding methods with novel neighborhood probabilities 1.2

by emstrick - August 20, 2013, 11:02:21 CET [ ] 16047 views, 4173 downloads, 0 subscriptions

About: Stochastic neighbor embedding originally aims at the reconstruction of given distance relations in a low-dimensional Euclidean space. This can be regarded as general approach to multi-dimensional scaling, but the reconstruction is based on the definition of input (and output) neighborhood probability alone. The present implementation also allows for handling dissimilarity or score-induced neighborhood topologies and makes use of quasi 2nd order gradient-based (l-)BFGS optimization.

Changes:

gradient in xsne_fun.m fixed! (constant factor m was missing)
symmetry option re-introduced allowing for enabling symmetric and asymmetric versions of SNE and t-SNE

Authors: Marc Strickert
License: Gnu Gpl V2
Programming Language: Matlab, Octave, Gpumat

Operating System: Platform Independent
Data Formats: Matlab
Tags: Dimension Reduction, Mds, Multidimensional Scaling, Sne, Stochastic Neighbor Embedding, Neighborhood Probability Estimation

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xSNE Stochastic Neighbor Embedding methods with novel neighborhood probabilities 1.2