Intelligent Database Systems Lab Presenter: YU-TING LU Authors: Laurens van der Maaten and Geoffrey...
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Transcript of Intelligent Database Systems Lab Presenter: YU-TING LU Authors: Laurens van der Maaten and Geoffrey...
Intelligent Database Systems Lab
Presenter: YU-TING LU
Authors: Laurens van der Maaten and Geoffrey Hinton
2012. ML
Visualizing non-metric similarities in multiple maps
Intelligent Database Systems Lab
Outlines
MotivationObjectivesMethodologyExperimentsConclusionsComments
Intelligent Database Systems Lab
Motivation• Techniques for multidimensional
scaling(MDS) are subject to the fundamental
limitations of metric spaces in a visualization.
• Multidimensional scaling cannot faithfully
represent intransitive pairwise similarities in
a visualization, and it cannot faithfully
visualize “central” objects.
Intelligent Database Systems Lab
Objectives• This study present an extension of multidimensional
scaling technique multiple maps t-SNE.
• The aims to address the problems of traditional
multidimensional scaling techniques when visualize
non-metric similarities.
• By constructing a collection of maps that reveal
complementary structure in the similarity data.
Intelligent Database Systems Lab
ExperimentsResults of multiple maps t-SNE on the word association data set(a-e)
Intelligent Database Systems Lab
ExperimentsResults of multiple maps t-SNE on the word association data set(a-e)
Intelligent Database Systems Lab
ExperimentsResults of multiple maps t-SNE on the word association data set(a-e)
Intelligent Database Systems Lab
ExperimentsResults of multiple maps t-SNE on the word association data set(a-e)
Intelligent Database Systems Lab
ExperimentsResults of multiple maps t-SNE on the word association data set(a-e)
Intelligent Database Systems Lab
ExperimentsResults of multiple maps t-SNE on the word association data set(a-e)
Intelligent Database Systems Lab
ExperimentsResults of multiple maps t-SNE on the NIPS co-authorship data set(a-d)
Intelligent Database Systems Lab
ExperimentsResults of multiple maps t-SNE on the NIPS co-authorship data set(a-d)
Intelligent Database Systems Lab
ExperimentsResults of multiple maps t-SNE on the NIPS co-authorship data set(a-d)
Intelligent Database Systems Lab
ExperimentsResults of multiple maps t-SNE on the NIPS co-authorship data set(a-d)
Intelligent Database Systems Lab
Conclusions
• This paper is to construct visualizations that are not
hampered by the two main limitations of metric spaces.
• Apply multiple maps t-SNE to a large data set of word
association data and to a data set of NIPS co-
authorships, demonstrating its ability to successfully
visualize non-metric similarities.