On the public citation graph

Privacy-preserving Cross-domain Recommendation with Federated Graph Learning

https://doi.org/10.1145/3653448
0 signed · 105 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-0-387-85820-3_1openalex-snapshot
Introduction to Recommender Systems Handbook
inferredcites →https://doi.org/10.1007/978-3-030-63076-8_16openalex-snapshot
Federated Recommendation Systems
inferredcites →https://doi.org/10.1007/978-3-540-73078-1_44openalex-snapshot
Cross-Domain Mediation in Collaborative Filtering
inferredcites →https://doi.org/10.1007/s00778-021-00700-6openalex-snapshot
Fast-adapting and privacy-preserving federated recommender system
inferredcites →https://doi.org/10.1007/s41666-020-00082-4openalex-snapshot
Federated Learning for Healthcare Informatics
inferredcites →https://doi.org/10.1016/j.compeleceng.2021.107213openalex-snapshot
A privacy-preserving framework for cross-domain recommender systems
inferredcites →https://doi.org/10.1016/j.dcan.2022.04.034openalex-snapshot
FedCDR: Privacy-preserving federated cross-domain recommendation
inferredcites →https://doi.org/10.1016/j.ins.2023.119976openalex-snapshot
FedGL: Federated graph learning framework with global self-supervision
inferredcites →https://doi.org/10.1109/access.2019.2896881openalex-snapshot
ACTL: Adaptive Codebook Transfer Learning for Cross-Domain Recommendation
inferredcites →https://doi.org/10.1109/access.2021.3091426openalex-snapshot
Privacy-Preserving Matrix Factorization for Cross-Domain Recommendation
inferredcites →https://doi.org/10.1109/ares.2008.85openalex-snapshot
Privacy-Preserving Recommendation Systems for Consumer Healthcare Services
inferredcites →https://doi.org/10.1109/bigdata47090.2019.9005983openalex-snapshot
SGNN: A Graph Neural Network Based Federated Learning Approach by Hiding Structure
inferredcites →https://doi.org/10.1109/icdm54844.2022.00060openalex-snapshot
GraphFL: A Federated Learning Framework for Semi-Supervised Node Classification on Graphs
inferredcites →https://doi.org/10.1109/ieeeconf56349.2022.10051918openalex-snapshot
Personalized Federated Recommender Systems with Private and Partially Federated AutoEncoders
inferredcites →https://doi.org/10.1109/infocom42981.2021.9488906openalex-snapshot
Device Sampling for Heterogeneous Federated Learning: Theory, Algorithms, and Implementation
inferredcites →https://doi.org/10.1109/infocomwkshps51825.2021.9484510openalex-snapshot
POI Recommendation with Federated Learning and Privacy Preserving in Cross Domain Recommendation
inferredcites →https://doi.org/10.1109/jbhi.2021.3069629openalex-snapshot
A Privacy-Preserving Cross-Domain Healthcare Wearables Recommendation Algorithm Based on Domain-Dependent and Domain-Independent Feature Fusion
inferredcites →https://doi.org/10.1109/jiot.2019.2952146openalex-snapshot
Local Differential Privacy for Deep Learning
inferredcites →https://doi.org/10.1109/mis.2020.3014880openalex-snapshot
Secure Federated Matrix Factorization
inferredcites →https://doi.org/10.1109/mis.2020.3017205openalex-snapshot
FedRec: Federated Recommendation With Explicit Feedback
inferredcites →https://doi.org/10.1109/tifs.2018.2812146openalex-snapshot
$\textsf{LoPub}$ : High-Dimensional Crowdsourced Data Publication With Local Differential Privacy
inferredcites →https://doi.org/10.1109/tkde.2021.3104873openalex-snapshot
A Unified Framework for Cross-Domain and Cross-System Recommendations
inferredcites →https://doi.org/10.1145/1401890.1401969openalex-snapshot
Relational learning via collective matrix factorization
inferredcites →https://doi.org/10.1145/1557019.1557090openalex-snapshot
Differentially private recommender systems
inferredcites →https://doi.org/10.1145/2020408.2020504openalex-snapshot
Localized factor models for multi-context recommendation
inferredcites →https://doi.org/10.1145/2736277.2741667openalex-snapshot
A Multi-View Deep Learning Approach for Cross Domain User Modeling in Recommendation Systems
inferredcites →https://doi.org/10.1145/2939672.2939673openalex-snapshot
Collaborative Knowledge Base Embedding for Recommender Systems
inferredcites →https://doi.org/10.1145/2976749.2978318openalex-snapshot
Deep Learning with Differential Privacy
inferredcites →https://doi.org/10.1145/3073565openalex-snapshot
Cross Domain Recommender Systems
inferredcites →https://doi.org/10.1145/3298981openalex-snapshot
Federated Machine Learning
inferredcites →https://doi.org/10.1145/3308558.3313538openalex-snapshot
Cross-domain Recommendation Without Sharing User-relevant Data
inferredcites →https://doi.org/10.1145/3314398openalex-snapshot
Privacy-preserving Cross-domain Location Recommendation
inferredcites →https://doi.org/10.1145/3340531.3412012openalex-snapshot
Cross Domain Recommendation via Bi-directional Transfer Graph Collaborative Filtering Networks
inferredcites →https://doi.org/10.1145/3357384.3357992openalex-snapshot
DTCDR
inferredcites →https://doi.org/10.1145/3397271.3401063openalex-snapshot
LightGCN
inferredcites →https://doi.org/10.1145/3404835.3462825openalex-snapshot
FedCT: Federated Collaborative Transfer for Recommendation
inferredcites →https://doi.org/10.1145/3404835.3463010openalex-snapshot
Transfer-Meta Framework for Cross-domain Recommendation to Cold-Start Users
inferredcites →https://doi.org/10.1145/3459637.3482016openalex-snapshot
RecBole: Towards a Unified, Comprehensive and Efficient Framework for Recommendation Algorithms
inferredcites →https://doi.org/10.1145/3477495.3531967openalex-snapshot
DisenCDR
inferredcites →https://doi.org/10.1145/3506715openalex-snapshot
FedCTR: Federated Native Ad CTR Prediction with Cross-platform User Behavior Data
inferredcites →https://doi.org/10.1145/3511808.3557320openalex-snapshot
FedCDR
inferredcites →https://doi.org/10.1145/3511808.3557680openalex-snapshot
RecBole 2.0: Towards a More Up-to-Date Recommendation Library
inferredcites →https://doi.org/10.1145/3534678.3539112openalex-snapshot
FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient Package for Federated Graph Learning
inferredcites →https://doi.org/10.1145/3534678.3539125openalex-snapshot
Contrastive Cross-domain Recommendation in Matching
inferredcites →https://doi.org/10.1145/3548455openalex-snapshot
A Survey on Cross-domain Recommendation: Taxonomies, Methods, and Future Directions
inferredcites →https://doi.org/10.1145/3583780.3615007openalex-snapshot
Periodicity May Be Emanative: Hierarchical Contrastive Learning for Sequential Recommendation
inferredcites →https://doi.org/10.1561/0400000042openalex-snapshot
The Algorithmic Foundations of Differential Privacy
inferredcites →https://doi.org/10.1609/aaai.v35i5.16546openalex-snapshot
FedRec++: Lossless Federated Recommendation with Explicit Feedback
inferredcites →https://doi.org/10.1631/fitee.1700813openalex-snapshot
Artificial intelligence and statistics
inferredcites →https://doi.org/10.17863/cam.89518openalex-snapshot
Optimal Client Sampling for Federated Learning
inferredcites →https://doi.org/10.18653/v1/2020.findings-emnlp.128openalex-snapshot
Privacy-Preserving News Recommendation Model Learning
inferredcites →https://doi.org/10.18653/v1/2021.findings-emnlp.124openalex-snapshot
Uni-FedRec: A Unified Privacy-Preserving News Recommendation Framework for Model Training and Online Serving
inferredcites →https://doi.org/10.24963/ijcai.2017/343openalex-snapshot
Cross-Domain Recommendation: An Embedding and Mapping Approach
inferredcites →https://doi.org/10.24963/ijcai.2021/639openalex-snapshot
Cross-Domain Recommendation: Challenges, Progress, and Prospects
inferredcites →https://doi.org/10.3390/electronics10172081openalex-snapshot
Communication Cost Reduction with Partial Structure in Federated Learning
inferredcites →https://doi.org/10.48550/arxiv.1901.09888openalex-snapshot
Federated Collaborative Filtering for Privacy-Preserving Personalized Recommendation System
inferredcites →https://doi.org/10.48550/arxiv.1909.12488openalex-snapshot
Improving Federated Learning Personalization via Model Agnostic Meta Learning
inferredcites →https://doi.org/10.48550/arxiv.1912.00818openalex-snapshot
Federated Learning with Personalization Layers
inferredcites →https://doi.org/10.48550/arxiv.2002.05516openalex-snapshot
Federated Learning of a Mixture of Global and Local Models
inferredcites →https://doi.org/10.48550/arxiv.2012.03214openalex-snapshot
TornadoAggregate: Accurate and Scalable Federated Learning via the Ring-Based Architecture
inferredcites →https://doi.org/10.48550/arxiv.2102.04925openalex-snapshot
FedGNN: Federated Graph Neural Network for Privacy-Preserving Recommendation
inferredcites →https://doi.org/10.48550/arxiv.2104.07145openalex-snapshot
FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks
inferredcites →https://doi.org/10.48550/arxiv.2106.13430openalex-snapshot
Subgraph Federated Learning with Missing Neighbor Generation
inferredcites →https://doi.org/10.52202/085713openalex-snapshot
Advances in Neural Information Processing Systems 19

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/978-3-032-09318-9_12openalex-snapshot
Privacy-Aware Knowledge Transfer for Cross-Domain Recommender System
inferred← citeshttps://doi.org/10.1007/978-981-92-0375-8_3openalex-snapshot
Mitigating Negative Transfer in Cross-Domain Sequential Recommendation: Collaborative Memory and Gradient-Feedback Reweighting
inferred← citeshttps://doi.org/10.1007/978-981-95-7141-3_13openalex-snapshot
PFRCRP: Parameter-Factorized Personalized Federated Recommendation for Cross-Domain Rating Predictions
inferred← citeshttps://doi.org/10.1007/s44163-025-00406-6openalex-snapshot
Educational resources recommendation algorithm based on GMF-MLP-NeuMF prediction model
inferred← citeshttps://doi.org/10.1016/j.comnet.2025.111243openalex-snapshot
Privacy-preserving cross-domain point-of-interests recommendation based on friendship in LBSs
inferred← citeshttps://doi.org/10.1016/j.comnet.2026.112427openalex-snapshot
Breaking the participation dilemma in decentralized federated learning: A multi-agent repeated game mechanism for edge networks
inferred← citeshttps://doi.org/10.1016/j.eswa.2024.125154openalex-snapshot
Efficient and adaptive secure cross-domain recommendations
inferred← citeshttps://doi.org/10.1016/j.eswa.2026.131335openalex-snapshot
FedCHG: Graph autoencoder enhanced federated learning for cross-Domain heterogeneous graph
inferred← citeshttps://doi.org/10.1016/j.eswa.2026.131910openalex-snapshot
Generalizable federated graph contrastive learning
inferred← citeshttps://doi.org/10.1016/j.inffus.2026.104712openalex-snapshot
Federated recommender systems as distributed knowledge fusion: Techniques, challenges, and future directions
inferred← citeshttps://doi.org/10.1016/j.ipm.2025.104485openalex-snapshot
Federated cross-domain CTR prediction with triple-view contrastive learning and LLM augmentation
inferred← citeshttps://doi.org/10.1016/j.ipm.2026.104722openalex-snapshot
Privacy-preserving heterogeneous graph representation learning for recommendation
inferred← citeshttps://doi.org/10.1016/j.knosys.2025.114349openalex-snapshot
Parsilo-CDR: Privacy-aware cross-domain recommendation for data silo
inferred← citeshttps://doi.org/10.1016/j.knosys.2025.114419openalex-snapshot
HBOFFS: Hybrid breeding optimization algorithm inspired federated feature selection for intrusion detection in IIoT
inferred← citeshttps://doi.org/10.1016/j.neucom.2025.132442openalex-snapshot
Federated intent-aware cross-domain recommendation via semantic alignment and collaborative enhancement
inferred← citeshttps://doi.org/10.1016/j.neunet.2025.108380openalex-snapshot
FedPCL-CDR: A federated prototype-based contrastive learning framework for privacy-preserving cross-domain recommendation
inferred← citeshttps://doi.org/10.1038/s41598-024-70032-2openalex-snapshot
Federated learning for network attack detection using attention-based graph neural networks
inferred← citeshttps://doi.org/10.1038/s41598-025-32127-2openalex-snapshot
A multi-source behavioral data framework for interpretable urban tourism forecasting
inferred← citeshttps://doi.org/10.1109/caibda70336.2026.11621657openalex-snapshot
Design and Implementation of a Cross-Domain Privacy-Preserving Recommendation System Based on Federated Learning
inferred← citeshttps://doi.org/10.1109/icairc68035.2025.11384983openalex-snapshot
Cross-Domain Recommendation with User Interest Alignment via Multimodal Feature Fusion
inferred← citeshttps://doi.org/10.1109/icbctis66509.2025.11387401openalex-snapshot
A Federated GNN-based Intent-aware Fair Recommendation Method
inferred← citeshttps://doi.org/10.1109/ngdn66208.2025.11182132openalex-snapshot
Design of Federated Recommendation Model and Data Privacy Protection Algorithm Based on Graph Convolutional Networks
inferred← citeshttps://doi.org/10.1109/satml68715.2026.00020openalex-snapshot
Position: Research in Collaborative Learning Does Not Serve Cross-Silo Federated Learning in Practice
inferred← citeshttps://doi.org/10.1109/tdsc.2026.3683950openalex-snapshot
Federated Latent Factorization of Tensors for Privacy-Preserving Representation Learning to Large-Scale Dynamic Weighted Directed Network
inferred← citeshttps://doi.org/10.1109/tkde.2025.3606643openalex-snapshot
Personalized Recommendation Models in Federated Settings: A Survey
inferred← citeshttps://doi.org/10.1109/tmm.2025.3543106openalex-snapshot
Federated User Preference Modeling for Privacy-Preserving Cross-Domain Recommendation
inferred← citeshttps://doi.org/10.1109/tnsm.2026.3691659openalex-snapshot
Federated Recommendation Model Based on Personalized Attention and Privacy-Preserving Dynamic Graph
inferred← citeshttps://doi.org/10.1109/tpami.2026.3711847openalex-snapshot
Aligning Condensed Graph via Hashing: A New Insight for Federated Graph Learning
inferred← citeshttps://doi.org/10.1109/wf-iot64238.2025.11270799openalex-snapshot
P2FGRec: Privacy-Preserving for Federated Graph Recommendation in Inter-Institutional Financial Data Exchange
inferred← citeshttps://doi.org/10.1145/3627673.3679595openalex-snapshot
The Devil is in the Sources! Knowledge Enhanced Cross-Domain Recommendation in an Information Bottleneck Perspective
inferred← citeshttps://doi.org/10.1145/3728359openalex-snapshot
Federated Semantic Learning for Privacy-preserving Cross-domain Recommendation
inferred← citeshttps://doi.org/10.1145/3742791openalex-snapshot
A Federated Graph Neural Network with Differential Privacy for Cross-domain Recommender Systems
inferred← citeshttps://doi.org/10.1145/3746252.3761270openalex-snapshot
DT-FedSDC: A Dual-Target Federated Framework with Semantic Enhancement and Disentangled Contrastive Learning for Cross-Domain Recommendation
inferred← citeshttps://doi.org/10.1145/3769811openalex-snapshot
P 2 FedRec: Towards Privacy-Preserving and Personalized Federated Recommendation via Relationship Awareness
inferred← citeshttps://doi.org/10.1145/3774904.3792533openalex-snapshot
Verifiable Federated Representation Learning for Cross-domain Sequential Recommendation
inferred← citeshttps://doi.org/10.1145/3774904.3792703openalex-snapshot
The Double-Edged Sword of Knowledge Transfer: Diagnosing and Curing Fairness Pathologies in Cross-Domain Recommendation
inferred← citeshttps://doi.org/10.1145/3803545openalex-snapshot
Privacy Matters: Data Attack to Make User Preferences Unlearnable in Recommendation
inferred← citeshttps://doi.org/10.1177/30504554251407092openalex-snapshot
User Profiling and Its Dynamics: A Narrative Review
inferred← citeshttps://doi.org/10.2139/ssrn.5799977openalex-snapshot
Learning from Tabular Data Silos without Data Sharing: A Contrastive Federated Learning Approach
inferred← citeshttps://doi.org/10.3390/app15052481openalex-snapshot
Personalized Federated Learning with Progressive Local Training Strategy and Lightweight Classifier
inferred← citeshttps://doi.org/10.4236/ojapps.2024.1411195openalex-snapshot
Federated Graph Learning Based on Graph Distance Computing
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.