Poisoning Self-supervised Learning Based Sequential Recommendations-Reference-Cited by-同舟云学术

Poisoning Self-supervised Learning Based Sequential Recommendations

Published:2023-07-18 Issue: Volume: Page:
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Container-title:Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval
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Author:

Wang Yanling¹^ORCID,Liu Yuchen¹^ORCID,Wang Qian²^ORCID,Wang Cong³^ORCID,Li Chenliang²^ORCID

Affiliation:

1. Wuhan University & City University of Hong Kong, Wuhan; Hong Kong, China

2. Wuhan University, Wuhan, China

3. City University of Hong Kong, Hong Kong, China

Funder

the Hong Kong RGC

National Natural Science Foundation of China

National Key R&D Program of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3539618.3591751

Reference61 articles.

1. Controlling Popularity Bias in Learning-to-Rank Recommendation

2. Classification features for attack detection in collaborative recommender systems

3. Nicholas Carlini and Andreas Terzis . 2022 . Poisoning and backdooring contrastive learning . In Proc. of ICLR. Nicholas Carlini and Andreas Terzis. 2022. Poisoning and backdooring contrastive learning. In Proc. of ICLR.

4. Knowledge-enhanced Black-box Attacks for Recommendations

5. Adversarial attacks on an oblivious recommender

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