2019/03/29 Deep Learning JP: http://deeplearning.jp/seminar-2/

1. 1
DEEP LEARNING JP
[DL Papers]
http://deeplearning.jp/
Hirono Okamoto, Matsuo Lab

2. : Deep Anomaly Detection Using Geometric Transformations
n NIPS 2018 accepted
n : Izhak Golan, Ran El-Yaniv
n :
n ( flip )
n
n AUROC OC-SVM, DAGMM, DSEBM, ADGAN SOTA
!"($) !&($) !'($) !(($)
( )
( )

3. :
n 1:
n 2:
1 (2 )
( )
( )

4. :
n
n
n One Class SVM

5. :
n (PCA, Robust-PCA, deep autoencoders, ADGAN…)
n
n One Class SVM
L2

6. :
n
n (KDE, Robust-KDE, DSEBM…)
n One Class SVM

7. :
n
n
n One Class SVM (SVDD, Deep SVDD...)

8. :
n
n
n
n or
n
λ

9. : step1
n k
n identity transformation
n
n x
cross-entropy
deep k-class
!"
72(=2x3x3x4)

10. : step2 Dirichlet Normality Score
n softmax y(x) (Dirichlet ) α
n α
x

11. :
step1:
step2: Dirichlet
α

12. :
n k f
n α y
n !"($)
!"($)

13. :
n One-Class SVM (OC-SVM)
n RAW-OC-SVM
n CAE-OC-SVM
n Deep One-Class Classification (E2E-OC-SVM)
n ICML2018
n Deep structured energy-based models (DSEBM)
n ICML 2016
n
n Deep Autoencoding Gaussian Mixture Model (DAGMM)
n ICLR 2018
n
n Anomaly Detection with a Generative Adversarial Network (ADGAN)
n AnoGAN(IPMI 2017)
n GAN

14. :
n CIFAR-10
n 10 6000 32x32
n CIFAR-100
n 100 600 32x32
n 20
n Fashion-MNIST
n 10 7000 28x28
n CatsVsDogs
n ASIRRA
n 2 12500 360x400 64x64

15. : AUROC
n AUROC(area under an ROC curve)
http://www.randpy.tokyo/entry/roc_auc
AUROC

16. : CIFAR-10
SOTA

17. : CIFAR-100
SOTA

18. : Fashion-MNIST CatsVsDogs
SOTA

19. n
n
n GAN SOTA
n
n ( ?)
n