Domain adaptation gan & transfer learning

1. Domain Adaptation

2. Why Domain Adaptation?

3. Domain Adaptation Application

4. Transfer Learning…?

5. Transfer Learning…?

6. Transfer Learning Methods in DL
Feature Extract Fine Tuning == re-weight Parameter Sharing

7. DA in DL
Just add one

8. Domain-Adversarial Neural Network
Classifier의 성능을 유지하면서
(Classifier)
source || target feature 분포도
고려,
Source에서 왔는지 Target에서
왔는지 알 수 없도록 방해
(GAN)

9. Domain-Adversarial Neural Network
GRL == -1

10. Domain-Adversarial Neural Network

11. Domain Separation Networks
Mapping Representations
One domain  Other domain
Extract Features
Invariant to the domain
Existing Approaches
Ignore the individual characteristics of each domain
Modeling What is…
1. Unique to each domain
2. Extract domain-invariant features
 private features
 shared features

12. Domain Separation Networks
domain adaptation 이기 때문에, source data
는 label 이 있지만 target data 는 label이 없음

13. Domain Separation Networks

14. Domain Separation Networks

15. Domain Separation Networks

16. Domain Separation Networks
RBF Kernel
GAN

17. Domain Separation Networks
GTSRB
MNIST

18. materials
• http://jaejunyoo.blogspot.com/2017/01/domain-
adversarial-training-of-neural.html
• http://cs231n.github.io/transfer-learning/
• https://www.cse.ust.hk/~qyang/Docs/2009/tkde_tr
ansfer_learning.pdf