Toward Adversarially Robust Recommendation From Adaptive Fraudster Detection
Author:
Affiliation:
1. Department of Computing, The Hong Kong Polytechnic University, Hung Hom, Hong Kong
2. Department of Industrial and System Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong
Funder
National Science Foundation of China
Hong Kong Research Grant Council
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Networks and Communications,Safety, Risk, Reliability and Quality
Link
http://xplorestaging.ieee.org/ielx7/10206/10319981/10296883.pdf?arnumber=10296883
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1. Matrix Factorization Techniques for Recommender Systems
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5. Attacking Fake News Detectors via Manipulating News Social Engagement
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