lemonviv / FedRecPapers

A project for collecting and showing the current research progress of FedRec

The existing papers about federated recommendation (FedRec)

This repository is maintained for collecting and showing the current research progress of FedRec.

Last Update: Feb. 22nd 2023.

Summary

Works are sorted by time.

Conference proceedings

Title	Time	Publication venue
The More the Merrier - Federated Learning from Local Sphere Recommendations	Sep. 2017	CD-MAKE'17
Decentralized Recommendation Based on Matrix Factorization: A Comparison of Gossip and Federated Learning	Sep. 2019	MLKDD-ECML PKDD'19
A Simple and Efficient Federated Recommender System	Dec. 2019	BDCAT'19
Federated Recommendation System via Differential Privacy	May. 2020	ISIT'20
Meta Matrix Factorization for Federated Rating Predictions	Jun. 2020	SIGIR'20
DPLCF: Differentially Private Local Collaborative Filtering	Jun. 2020	SIGIR'20
Federated CF: Privacy-Preserving Collaborative Filtering Cross Multiple Datasets	Jun. 2020	ICC'20
FedFast: Going beyond Average for Faster Training of Federated Recommender Systems	Aug. 2020	KDD'20
Secure Efficient Federated KNN for Recommendation Systems	Aug. 2020	ICNC-FSKD‘20
Secure Social Recommendation based on Secret Sharing	Aug. 2020	ECAI‘20
A Federated Recommender System for Online Services	Sep. 2020	RecSys‘20
Privacy-Preserving News Recommendation Model Learning	Oct. 2020	EMNLP'20
FedRec++: Lossless Federated Recommendation with Explicit Feedback	Dec. 2020	AAAI'21
Federated Multi-Armed Bandits	Dec. 2020	AAAI'21
Personalized Recommendation Algorithm for Mobile Based on Federated Matrix Factorization	Mar. 2021	CDMMS'20
FedeRank: User Controlled Feedback with Federated Recommender Systems	Mar. 2021	ECIR 2021
Federated Multi-armed Bandits with Personalization	Apr. 2021	AISTATS'21
Vertical Federated Learning for Higher-Order Factorization Machines	May 2021	PAKDD'21
Demystifying Model Averaging for Communication-Efficient Federated Matrix Factorization	Jun. 2021	ICASSP'21
A Payload Optimization Method for Federated Recommender Systems	Sep. 2021	RecSys‘21
Stronger Privacy for Federated Collaborative Filtering With Implicit Feedback	Sep. 2021	RecSys‘21
FR-FMSS: Federated Recommendation via Fake Marks and Secret Sharing	Sep. 2021	RecSys‘21
Federated Recommender Systems with Learning to Rank	Sep. 2021	SEBD‘21
A vertical federation recommendation method based on clustering and latent factor model	Sep. 2021	EIECS'21
Federated Learning Application on Telecommunication-Joint Healthcare Recommendation	Oct. 2021	ICCT‘21
Exploiting Data Sparsity in Secure Cross-Platform Social Recommendation	Dec. 2021	NeurIPS'21
PipAttack: Poisoning Federated Recommender Systems for Manipulating Item Promotion	Feb. 2022	WSDM'22
Differential Private Knowledge Transfer for Privacy-Preserving Cross-Domain Recommendation	Apr. 2022	WWW'22
FedAttack: Effective and Covert Poisoning Attack on Federated Recommendation via Hard Sampling	Aug. 2022	KDD'22
Fairness-aware Federated Matrix Factorization	Sep. 2022	RecSys'22
Towards Fair Federated Recommendation Learning: Characterizing the Inter-Dependence of System and Data Heterogeneity	Sep. 2022	RecSys'22

Journal articles

Title	Time	Publication venue
A Privacy-Preserving Distributed Contextual Federated Online Learning Framework with Big Data Support in Social Recommender Systems	Aug. 2019	TKDE
FedRec: Federated Recommendation with Explicit Feedback	Aug. 2020	IEEE Intelligent Systems
Secure Federated Matrix Factorization	Aug. 2020	IEEE Intelligent Systems
Differentially private locality sensitive hashing based federated recommender system	Feb. 2021	Concurrency and Computation: Practice and Experience
Personalized Recommendation Algorithm for Mobile Based on Federated Matrix Factorization	Mar. 2021	Journal of Physics: Conference Series
A Federated Learning Approach for Privacy Protection in Context-Aware Recommender Systems	Apr. 2021	The Computer Journal
DARES: An Asynchronous Distributed Recommender System Using Deep Reinforcement Learning	Jun. 2021	IEEE Access
Federated matrix factorization for privacy-preserving recommender systems	Jul. 2021	Applied Soft Computing
FedDSR: Daily Schedule Recommendation in a Federated Deep Reinforcement Learning Framework	Nov. 2021	TKDE
Efficient Federated Matrix Factorization against Inference Attacks	May. 2022	TIST
FedCDR: Privacy-preserving federated cross-domain recommendation	May. 2022	TIST
Federated recommenders: methods, challenges and future	May. 2022	Cluster Computing
FedRec: Trusted rank-based recommender scheme for service provisioning in federated cloud environment	Jun. 2022	Digital Communications and Networks
Privacy-Preserving Hierarchical Federated Recommendation Systems	Feb. 2023	IEEE Communications Letters

Book chapters

Title	Time	Publication venue
Federated Recommendation Systems	Dec. 2020	FLPI'20

Workshop papers

Title	Time	Publication venue
Secure Federated Matrix Factorization	Jun. 2019	Fl-IJCAI'19
Privacy Threats Against Federated Matrix Factorization	Jul. 2020	FL-IJCAI'20

arXiv e-prints

Title	Time	Publication venue
Federated Collaborative Filtering for Privacy-Preserving Personalized Recommendation System	Jan. 2019	arXiv
Federating Recommendations Using Differentially Private Prototypes	Mar. 2020	arXiv
Federated Multi-view Matrix Factorization for Personalized Recommendations	Apr. 2020	arXiv
Robust Federated Recommendation System	Jun. 2020	arXiv
A Federated Multi-View Deep Learning Framework for Privacy-Preserving Recommendations	Aug. 2020	arXiv
Shared MF: A privacy-preserving recommendation system	Aug. 2020	arXiv
A Novel Privacy-Preserved Recommender System Framework based on Federated Learning	Nov. 2020	arXiv
Fast-adapting and Privacy-preserving Federated Recommender System	Apr. 2021	arXiv
Stronger Privacy for Federated Collaborative Filtering with Implicit Feedback	May. 2021	arXiv
Federated Neural Collaborative Filtering	Jun. 2021	arXiv
Practical and Secure Federated Recommendation with Personalized Masks	Aug. 2021	arXiv
PipAttack: Poisoning Federated Recommender Systems for Manipulating Item Promotion	Oct. 2021	arXiv
FedSPLIT: One-Shot Federated Recommendation System Based on Non-negative Joint Matrix Factorization and Knowledge Distillation	May. 2022	arXiv