Privacy-preserving recommender system using the data collaboration analysis for distributed datasets

24 May 2024

Papers citing "Privacy-preserving recommender system using the data collaboration analysis for distributed datasets"

8 / 8 papers shown

Title
ReFRS: Resource-efficient Federated Recommender System for Dynamic and Diversified User Preferences Mubashir Imran Hongzhi Yin Tong Chen Nguyen Quoc Viet Hung Alexander Zhou Kai Zheng 48 70 0 28 Jul 2022
LightFR: Lightweight Federated Recommendation with Privacy-preserving Matrix Factorization Honglei Zhang Fangyuan Luo Jun Wu Xiangnan He Yidong Li 41 81 0 23 Jun 2022
Federated Social Recommendation with Graph Neural Network Zhiwei Liu Liangwei Yang Ziwei Fan Hao Peng Philip S. Yu FedML 65 154 0 21 Nov 2021
Accuracy and Privacy Evaluations of Collaborative Data Analysis A. Imakura A. Bogdanova Takaya Yamazoe Kazumasa Omote Tetsuya Sakurai 34 13 0 27 Jan 2021
Graph Neural Networks in Recommender Systems: A Survey Shiwen Wu Fei Sun Wentao Zhang Xu Xie Tengjiao Wang GNN 123 1,225 0 04 Nov 2020
Optuna: A Next-generation Hyperparameter Optimization Framework Takuya Akiba Shotaro Sano Toshihiko Yanase Takeru Ohta Masanori Koyama 625 5,769 0 25 Jul 2019
Differential Privacy Has Disparate Impact on Model Accuracy Eugene Bagdasaryan Vitaly Shmatikov 137 480 0 28 May 2019
Federated Collaborative Filtering for Privacy-Preserving Personalized Recommendation System Muhammad Ammad-ud-din E. Ivannikova Suleiman A. Khan Were Oyomno Qiang Fu K. E. Tan Adrian Flanagan FedML 66 271 0 29 Jan 2019