Adversarial robustness of deep reinforcement learning based dynamic recommender systems

HIGHLIGHTS

• who: Lina Yao from the School of Computer Science and Engineering, University of New South Wales, Sydney, NSW, Australia, School of have published the Article: Adversarial Robustness of Deep Reinforcement Learning Based Dynamic Recommender Systems, in the Journal: (JOURNAL)
• what: The authors propose an encoder-classification detection model for attack-agnostic detection. This is the study that focuses on the adversarial detection of RL-based Recommendation Systems. The authors explore the test-time white-box attack for the RL-based recommender system. The authors aim to build a model with the generalization ability to detect . . .
  

   

  

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