Trusted and Responsible AI - Explainability, Adversarial Attacks, Bias, and Fairness

Trusted and Responsible AI - Explainability, Adversarial Attacks, Bias, and Fairness

Linux Foundation via YouTube Direct link

Poisoning attacks

10 of 15

10 of 15

Poisoning attacks

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Trusted and Responsible AI - Explainability, Adversarial Attacks, Bias, and Fairness

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  1. 1 OPEN SOURCE SUMMIT
  2. 2 Speaker Profile
  3. 3 Introduction
  4. 4 The Principles of responsible Al
  5. 5 Why XAI is important?
  6. 6 Adversarial Machine Learning Defenses
  7. 7 Adversarial training
  8. 8 Switching models
  9. 9 Generalised models
  10. 10 Poisoning attacks
  11. 11 Evasion attacks
  12. 12 Model stealing
  13. 13 Methods of combating attacks
  14. 14 Fixing biases in Al and machine learning algorithms
  15. 15 Conclusion

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