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Publication search results
found 54 matches
- 2024
- Fatemeh Rezaimehr, Chitra Dadkhah:
T&TRS: robust collaborative filtering recommender systems against attacks. Multim. Tools Appl. 83(11): 31701-31731 (2024) - Filippo Betello, Federico Siciliano, Pushkar Mishra, Fabrizio Silvestri:
Investigating the Robustness of Sequential Recommender Systems Against Training Data Perturbations. ECIR (2) 2024: 205-220 - Shanshan Zhong, Zhongzhan Huang, Daifeng Li, Wushao Wen, Jinghui Qin, Liang Lin:
Mirror Gradient: Towards Robust Multimodal Recommender Systems via Exploring Flat Local Minima. WWW 2024: 3700-3711 - Shanshan Zhong, Zhongzhan Huang, Daifeng Li, Wushao Wen, Jinghui Qin, Liang Lin:
Mirror Gradient: Towards Robust Multimodal Recommender Systems via Exploring Flat Local Minima. CoRR abs/2402.11262 (2024) - Kexin Shi, Jing Zhang, Linjiajie Fang, Wenjia Wang, Bingyi Jing:
Enhanced Bayesian Personalized Ranking for Robust Hard Negative Sampling in Recommender Systems. CoRR abs/2403.19276 (2024) - Tomoya Yanagi, Shunnosuke Ikeda, Yuichi Takano:
Robust portfolio optimization for recommender systems considering uncertainty of estimated statistics. CoRR abs/2406.10250 (2024) - 2023
- Chenwang Wu, Defu Lian, Yong Ge, Zhihao Zhu, Enhong Chen:
Influence-Driven Data Poisoning for Robust Recommender Systems. IEEE Trans. Pattern Anal. Mach. Intell. 45(10): 11915-11931 (2023) - Junruo Gao, Yuyang Liu, Zhaojuan Yue, Haibo Wu, Jun Li:
Robust Preference Learning for Recommender Systems under Purchase Behavior Shifts. CSCWD 2023: 1728-1733 - Le Nguyen Hoai Nam:
A Robust Approach for Hybrid Personalized Recommender Systems. TPDL 2023: 160-172 - Min Gao, Ke-Jing Du, Pei-Yao Zhu, Jian-Yu Li, Hua Wang, Zhi-Hui Zhan:
A Robust Two-Part Modeling Strategy for Knowledge Graph Enhanced Recommender Systems. ICACI 2023: 1-7 - Jinyuan Jia, Yupei Liu, Yuepeng Hu, Neil Zhenqiang Gong:
PORE: Provably Robust Recommender Systems against Data Poisoning Attacks. USENIX Security Symposium 2023: 1703-1720 - Ali Montazeralghaem, James Allan:
Evaluating the Robustness of Conversational Recommender Systems by Adversarial Examples. CoRR abs/2303.05575 (2023) - Jinyuan Jia, Yupei Liu, Yuepeng Hu, Neil Zhenqiang Gong:
PORE: Provably Robust Recommender Systems against Data Poisoning Attacks. CoRR abs/2303.14601 (2023) - Melissa Mozifian, Tristan Sylvain, Dave Evans, Lili Meng:
Robust Reinforcement Learning Objectives for Sequential Recommender Systems. CoRR abs/2305.18820 (2023) - Filippo Betello, Federico Siciliano, Pushkar Mishra, Fabrizio Silvestri:
Investigating the Robustness of Sequential Recommender Systems Against Training Data Perturbations: an Empirical Study. CoRR abs/2307.13165 (2023) - 2022
- Siyu Wang, Yuanjiang Cao, Xiaocong Chen, Lina Yao, Xianzhi Wang, Quan Z. Sheng:
Adversarial Robustness of Deep Reinforcement Learning Based Dynamic Recommender Systems. Frontiers Big Data 5 (2022) - Onkar Malgonde, He Zhang, Balaji Padmanabhan, Moez Limayem:
Managing Digital Platforms with Robust Multi-Sided Recommender Systems. J. Manag. Inf. Syst. 39(4): 938-968 (2022) - Qingyang Wang, Defu Lian, Chenwang Wu, Enhong Chen:
Towards Robust Recommender Systems via Triple Cooperative Defense. WISE 2022: 564-578 - Zohreh Ovaisi, Shelby Heinecke, Jia Li, Yongfeng Zhang, Elena Zheleva, Caiming Xiong:
RGRecSys: A Toolkit for Robustness Evaluation of Recommender Systems. WSDM 2022: 1597-1600 - Teng Xiao, Suhang Wang:
Towards Unbiased and Robust Causal Ranking for Recommender Systems. WSDM 2022: 1158-1167 - Zohreh Ovaisi, Shelby Heinecke, Jia Li, Yongfeng Zhang, Elena Zheleva, Caiming Xiong:
RGRecSys: A Toolkit for Robustness Evaluation of Recommender Systems. CoRR abs/2201.04399 (2022) - Bingbing Wen, Yunhe Feng, Yongfeng Zhang, Chirag Shah:
Towards Generating Robust, Fair, and Emotion-Aware Explanations for Recommender Systems. CoRR abs/2208.08017 (2022) - Qingyang Wang, Defu Lian, Chenwang Wu, Enhong Chen:
Towards Robust Recommender Systems via Triple Cooperative Defense. CoRR abs/2210.13762 (2022) - 2021
- João Vinagre, Alípio Mário Jorge, Conceição Rocha, João Gama:
Statistically Robust Evaluation of Stream-Based Recommender Systems. IEEE Trans. Knowl. Data Eng. 33(7): 2971-2982 (2021) - Yashar Deldjoo, Tommaso Di Noia, Eugenio Di Sciascio, Felice Antonio Merra:
A Regression Framework to Interpret the Robustness of Recommender Systems Against Shilling Attacks. IIR 2021 - Anu Shrestha, Francesca Spezzano, Maria Soledad Pera:
An Empirical Analysis of Collaborative Recommender Systems Robustness to Shilling Attacks. OHARS@RecSys 2021: 45-57 - Chenwang Wu, Defu Lian, Yong Ge, Zhihao Zhu, Enhong Chen, Senchao Yuan:
Fight Fire with Fire: Towards Robust Recommender Systems via Adversarial Poisoning Training. SIGIR 2021: 1074-1083 - Siyu Wang, Yuanjiang Cao, Xiaocong Chen, Lina Yao, Xianzhi Wang, Quan Z. Sheng:
Adversarial Robustness of Deep Reinforcement Learning based Dynamic Recommender Systems. CoRR abs/2112.00973 (2021) - 2020
- Jia Wang, Min Gao, Zongwei Wang, Runsheng Wang, Junhao Wen:
Robustness Analysis of Triangle Relations Attack in Social Recommender Systems. CLOUD 2020: 557-565 - Chengying Mao, Xiaorong Yi, Tsong Yueh Chen:
Metamorphic Robustness Testing for Recommender Systems: A Case Study. DSA 2020: 331-336
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