Stronger Privacy for Federated Collaborative Filtering with Implicit
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Stronger Privacy for Federated Collaborative Filtering with Implicit Feedback

9 May 2021

Hamed Haddadi

Papers citing "Stronger Privacy for Federated Collaborative Filtering with Implicit Feedback"

8 / 8 papers shown

Title
Preventing the Popular Item Embedding Based Attack in Federated Recommendations Junxuan Zhang Huan Li Dazhong Rong Yan Zhao Ke Chen Lidan Shou AAML 80 4 0 18 Feb 2025
Federated Privacy-preserving Collaborative Filtering for On-Device Next App Prediction A. Sayapin Gleb Balitskiy Daniel Bershatsky Aleksandr Katrutsa Evgeny Frolov Alexey Frolov Ivan Oseledets Vitaliy N. Kharin FedML 31 1 0 05 Feb 2023
Modeling Global Distribution for Federated Learning with Label Distribution Skew Tao Sheng Cheng Shen Yuan Liu Yeyu Ou Zhe Qu Jianxin Wang FedML 27 7 0 17 Dec 2022
FedGRec: Federated Graph Recommender System with Lazy Update of Latent Embeddings Junyi Li Heng-Chiao Huang FedML 24 6 0 25 Oct 2022
Cali3F: Calibrated Fast Fair Federated Recommendation System Zhitao Zhu Shijing Si Jianzong Wang Jing Xiao FedML 81 14 0 26 May 2022
Backdoor Attacks in Federated Learning by Rare Embeddings and Gradient Ensembling Kiyoon Yoo Nojun Kwak SILM AAML FedML 33 19 0 29 Apr 2022
FedRecAttack: Model Poisoning Attack to Federated Recommendation Dazhong Rong Shuai Ye Ruoyan Zhao Hon Ning Yuen Jianhai Chen Qinming He AAML FedML 24 57 0 01 Apr 2022
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity Ulfar Erlingsson Vitaly Feldman Ilya Mironov A. Raghunathan Kunal Talwar Abhradeep Thakurta 150 420 0 29 Nov 2018