Γ-SNE for feed-forward data visualisation

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Abstract

t-distributed Stochastic Neighbour Embedding (t-SNE) is one of the most popular nonlinear dimension reduction techniques used in multiple application domains. In this paper we propose a variation on the embedding neighbourhood distribution, resulting in Γ-SNE, which can construct a feed-forward mapping using an RBF network. We compare the visualizations generated by Γ-SNE with those of t-SNE and provide empirical evidence suggesting the network is capable of robust interpolation and automatic weight regularization.

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  • Gamma-SNE for feed-forward data visualisation

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Original languageEnglish
JournalInformation Visualization
Volumeaccepted
StateAccepted/In press - 2016

Employable Graduates; Exploitable Research

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