1. Intelligent Database Systems Lab Presenter: HONG, CHIA-TSE Authors:Yang Liu, Yan Liu, Keith C. C. Chan, Kien A. Hua 2014. TONNAL. Hybrid Manifold Embedding

2. Intelligent Database Systems Lab Outlines Motivation Objectives Methodology Experiments Conclusions Comments 1

3. Intelligent Database Systems Lab Motivation Most of the existing supervised manifold learning algorithms that give linear explicit mapping function. 2

4. Intelligent Database Systems Lab Objectives This study present a novel supervised manifold learning framework dubbed hybrid manifold embedding. HyME aims to provide a more general nonlinear explicit mapping function by performing a tow-layer learning procedure. 3

5. Intelligent Database Systems Lab Methodology 4

6. Intelligent Database Systems Lab Methodology 5

7. Intelligent Database Systems Lab Methodology 6

8. Intelligent Database Systems Lab Methodology 7

9. Intelligent Database Systems Lab Methodology 8

10. Intelligent Database Systems Lab Methodology 9

11. Intelligent Database Systems Lab Methodology 10

12. Intelligent Database Systems Lab Experiment 11 LPGC+LCDPK-means+ LCDP

13. Intelligent Database Systems Lab Experiment USPS Digit Data Set 12 PCA LDA SOLPPHyME, c=1 LPP HyME, c=2 LPMIP

14. Intelligent Database Systems Lab Experiment 13

15. Intelligent Database Systems Lab Experiment HyME, C=2 14

16. Intelligent Database Systems Lab Experiment 15 GC+LCDP

17. Intelligent Database Systems Lab Experiment K=3,4,5 時 績效很類似 C>2 績效下 降 16 K=2 K=5K=4 K=3

18. Intelligent Database Systems Lab Experiment 17

19. Intelligent Database Systems Lab Conclusions HyME provides a nonlinear explicit mapping function by performing a two-layer learning procedure. In the experiments, HyME get a good performance.

20. Intelligent Database Systems Lab Comments Advantages - Providing a more general nonlinear explicit mapping function