PORE: Provably Robust Recommender Systems against Data Poisoning Attacks

26 March 2023

Papers citing "PORE: Provably Robust Recommender Systems against Data Poisoning Attacks"

8 / 8 papers shown

Title
Deterministic Certification of Graph Neural Networks against Graph Poisoning Attacks with Arbitrary Perturbations Jiate Li Meng Pang Yun Dong Binghui Wang AAML 67 0 0 24 Mar 2025
Advancements in Recommender Systems: A Comprehensive Analysis Based on Data, Algorithms, and Evaluation Xin Ma Mingyue Li Xuguang Liu OffRL 33 0 0 10 Jul 2024
Leakage-Resilient and Carbon-Neutral Aggregation Featuring the Federated AI-enabled Critical Infrastructure Zehang Deng Ruoxi Sun Minhui Xue Sheng Wen S. Çamtepe Surya Nepal Yang Xiang 39 1 0 24 May 2024
Manipulating Recommender Systems: A Survey of Poisoning Attacks and Countermeasures Thanh Toan Nguyen Quoc Viet Hung Nguyen Thanh Tam Nguyen T. T. Huynh Thanh Thi Nguyen Matthias Weidlich Hongzhi Yin AAML 29 21 0 23 Apr 2024
FCert: Certifiably Robust Few-Shot Classification in the Era of Foundation Models Yanting Wang Wei Zou Jinyuan Jia 47 1 0 12 Apr 2024
Collective Certified Robustness against Graph Injection Attacks Y. Lai Bailin Pan Kaihuang Chen Yancheng Yuan Kai Zhou AAML 35 2 0 03 Mar 2024
Preference Poisoning Attacks on Reward Model Learning Junlin Wu Jiong Wang Chaowei Xiao Chenguang Wang Ning Zhang Yevgeniy Vorobeychik AAML 24 5 0 02 Feb 2024
Node-aware Bi-smoothing: Certified Robustness against Graph Injection Attacks Y. Lai Yulin Zhu Bailin Pan Kai Zhou AAML 36 6 0 07 Dec 2023