1. 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

2. Intelligent Database Systems Lab Outlines Motivation Objectives Methodology Experiments Conclusions Comments

3. 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.

4. 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.

5. Intelligent Database Systems Lab Methodology(review: t-SNE)

6. Intelligent Database Systems Lab Methodology-Multiple maps t-SNE

7. Intelligent Database Systems Lab Experiments Results of multiple maps t-SNE on the word association data set(a-e)

8. Intelligent Database Systems Lab Experiments Results of multiple maps t-SNE on the word association data set(a-e)

9. Intelligent Database Systems Lab Experiments Results of multiple maps t-SNE on the word association data set(a-e)

10. Intelligent Database Systems Lab Experiments Results of multiple maps t-SNE on the word association data set(a-e)

11. Intelligent Database Systems Lab Experiments Results of multiple maps t-SNE on the word association data set(a-e)

12. Intelligent Database Systems Lab Experiments Results of multiple maps t-SNE on the word association data set(a-e)

13. Intelligent Database Systems Lab Experiments

14. Intelligent Database Systems Lab Experiments Results of multiple maps t-SNE on the NIPS co-authorship data set(a-d)

15. Intelligent Database Systems Lab Experiments Results of multiple maps t-SNE on the NIPS co-authorship data set(a-d)

16. Intelligent Database Systems Lab Experiments Results of multiple maps t-SNE on the NIPS co-authorship data set(a-d)

17. Intelligent Database Systems Lab Experiments Results of multiple maps t-SNE on the NIPS co-authorship data set(a-d)

18. Intelligent Database Systems Lab Experiments

19. 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.

20. Intelligent Database Systems Lab Comments Advantages - Faithfully visualizing non-metric similarity data Applications - Data visualization. - Non-metric similarities.