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[DL輪読会]Deep Anomaly Detection Using Geometric Transformations

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Published on

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

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[DL輪読会]Deep Anomaly Detection Using Geometric Transformations

  1. 1. 1 DEEP LEARNING JP [DL Papers] http://deeplearning.jp/ Hirono Okamoto, Matsuo Lab
  2. 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. 3. : n 1: n 2: 1 (2 ) ( ) ( )
  4. 4. : n n n One Class SVM
  5. 5. : n (PCA, Robust-PCA, deep autoencoders, ADGAN…) n n One Class SVM L2
  6. 6. : n n (KDE, Robust-KDE, DSEBM…) n One Class SVM
  7. 7. : n n n One Class SVM (SVDD, Deep SVDD...)
  8. 8. : n n n n or n λ
  9. 9. : step1 n k n identity transformation n n x cross-entropy deep k-class !" 72(=2x3x3x4)
  10. 10. : step2 Dirichlet Normality Score n softmax y(x) (Dirichlet ) α n α x
  11. 11. : step1: step2: Dirichlet α
  12. 12. : n k f n α y n !"($) !"($)
  13. 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. 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. 15. : AUROC n AUROC(area under an ROC curve) http://www.randpy.tokyo/entry/roc_auc AUROC
  16. 16. : CIFAR-10 SOTA
  17. 17. : CIFAR-100 SOTA
  18. 18. : Fashion-MNIST CatsVsDogs SOTA
  19. 19. n n n GAN SOTA n n ( ?) n

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