Table of Contents
keywords
Statistics: π₯ code is available & stars >= 100 | β citation >= 50 | π Top-tier venue
kg.
: Knowledge Graphβ| data.
: dataset β| β surv.
: survey
Update log
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2022/07/12 - Give a list of papers in the field of federated learning in top journals
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2022/05/25 - complete the paper and code lists of FL on tabular data and Tree algorithms
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2022/05/25 - add the paper list of FL on tabular data and Tree algorithms
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2022/05/24 - complete the paper and code lists of FL on graph data and Graph Neural Networks
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2022/05/23 - add the paper list of FL on graph data and Graph Neural Networks
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2022/05/21 - update all of Federated Learning Framework
This section partially refers to DBLP search engine and repositories Awesome-Federated-Learning-on-Graph-and-GNN-papers and Awesome-Federated-Machine-Learning.
Title | Venue | Year | Materials |
---|---|---|---|
Deep Neural Network Fusion via Graph Matching with Applications to Model Ensemble and Federated Learning | ICML π | 2022 | [PUB.] [Code] |
FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient Package for Federated Graph Learning π₯ | KDD π | 2022 | [PDF] [Code] |
Meta-Learning Based Knowledge Extrapolation for Knowledge Graphs in the Federated Setting kg. |
IJCAI π | 2022 | [PDF] [Code] |
SpreadGNN: Serverless Multi-task Federated Learning for Graph Neural Networks | AAAI π | 2022 | [PDF] [Code] |
A federated graph neural network framework for privacy-preserving personalization | Nature Communications | 2022 | [PUB.] |
Efficient Federated Learning on Knowledge Graphs via Privacy-preserving Relation Embedding Aggregation kg. |
ACL Workshop | 2022 | [PDF] [Code] |
Power Allocation for Wireless Federated Learning using Graph Neural Networks | ICASSP | 2022 | [PDF] [PUB.] [Code] |
Privacy-Preserving Federated Multi-Task Linear Regression: A One-Shot Linear Mixing Approach Inspired By Graph Regularization | ICASSP | 2022 | [PUB.] |
Graph-Based Traffic Forecasting via Communication-Efficient Federated Learning | WCNC | 2022 | [PUB.] |
Malicious Transaction Identification in Digital Currency via Federated Graph Deep Learning | INFOCOM Workshops | 2022 | [PUB.] |
Federated learning of molecular properties with graph neural networks in a heterogeneous setting | Patterns | 2022 | [PUB.] |
Decentralized Graph Federated Multitask Learning for Streaming Data | CISS | 2022 | [PUB.] |
Dynamic Neural Graphs Based Federated Reptile for Semi-Supervised Multi-Tasking in Healthcare Applications | JBHI | 2022 | [PDF] |
Federated Knowledge Graphs Embedding kg. |
CIKM | 2021 | [PDF] [Code] |
Federated Graph Classification over Non-IID Graphs | NeurIPS π | 2021 | [PDF] [PUB.] [Code] |
FL-DISCO: Federated Generative Adversarial Network for Graph-based Molecule Drug Discovery: Special Session Paper | ICCAD | 2021 | [PUB.] |
DAG-FL: Direct Acyclic Graph-based Blockchain Empowers On-Device Federated Learning | ICC | 2021 | [PUB.] |
Graphical Federated Cloud Sharing Markets | TSUSC | 2021 | [PUB.] |
Virtual Knowledge Graphs for Federated Log Analysis kg. |
ARES | 2021 | [PUB.] |
FedE: Embedding Knowledge Graphs in Federated Setting kg. |
IJCKG | 2021 | [PDF] [PUB.][Code] |
Federated Knowledge Graph Embeddings with Heterogeneous Data kg. |
CCKS | 2021 | [PUB.] |
A Graph Federated Architecture with Privacy Preserving Learning | SPAWC | 2021 | [PDF] [PUB.] |
Federated Social Recommendation with Graph Neural Network | ACM TIST | 2021 | [PDF] |
Subgraph Federated Learning with Missing Neighbor Generation | NeurIPS π | 2021 | [PDF] [PUB.] |
Cross-Node Federated Graph Neural Network for Spatio-Temporal Data Modeling | KDD π | 2021 | [PDF] [Code] |
FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks π₯ surv. |
ICLR-DPML | 2021 | [PDF] [Code] |
Cluster-driven Graph Federated Learning over Multiple Domains | CVPR Workshop | 2021 | [PDF] |
Differentially Private Federated Knowledge Graphs Embedding kg. |
CIKM | 2021 | [PDF] [Code] |
Glint: Decentralized Federated Graph Learning with Traffic Throttling and Flow Scheduling | IWQoS | 2021 | [PUB.] |
A Federated Multigraph Integration Approach for Connectional Brain Template Learning | MICCAI Workshop | 2021 | [PDF] |
FedGraph: Federated Graph Learning with Intelligent Sampling | TPDS π | 2021 | [PDF] |
Federated Graph Neural Network for Cross-graph Node Classification | CCIS | 2021 | [PUB.] |
GraFeHTy: Graph Neural Network using Federated Learning for Human Activity Recognition | ICMLA | 2021 | [PUB.] |
ASFGNN: Automated Separated-Federated Graph Neural Network | PPNA | 2020 | [PDF] [PUB.] |
Towards Federated Graph Learning for Collaborative Financial Crimes Detection | NeurIPS Workshop | 2019 | [PDF] |
FedGNN: Federated Graph Neural Network for Privacy-Preserving Recommendation | ICML workshop | 2021 | [PDF] |
SGNN: A Graph Neural Network Based Federated Learning Approach by Hiding Structure | BigData | 2019 | [PDF] [PUB.] |
Privacy-preserving Graph Analytics: Secure Generation and Federated Learning | preprint | 2022 | [PDF] |
Personalized Subgraph Federated Learning | preprint | 2022 | [PDF] |
Federated Graph Attention Network for Rumor Detection | preprint | 2022 | [PDF] [Code] |
A Privacy-Preserving Subgraph-Level Federated Graph Neural Network via Differential Privacy | preprint | 2022 | [PDF] |
FedRel: An Adaptive Federated Relevance Framework for Spatial Temporal Graph Learning | preprint | 2022 | [PDF] |
Privatized Graph Federated Learning | preprint | 2022 | [PDF] |
Graph-Assisted Communication-Efficient Ensemble Federated Learning | preprint | 2022 | [PDF] |
Federated Graph Neural Networks: Overview, Techniques and Challenges surv. |
preprint | 2022 | [PDF] |
More is Better (Mostly): On the Backdoor Attacks in Federated Graph Neural Networks | preprint | 2022 | [PDF] |
FedGCN: Convergence and Communication Tradeoffs in Federated Training of Graph Convolutional Networks | preprint | 2022 | [PDF] [Code] |
Federated Learning with Heterogeneous Architectures using Graph HyperNetworks | preprint | 2022 | [PDF] |
FedNI: Federated Graph Learning with Network Inpainting for Population-Based Disease Prediction | preprint | 2021 | [PDF] |
STFL: A Temporal-Spatial Federated Learning Framework for Graph Neural Networks | preprint | 2021 | [PDF] [Code] |
Graph-Fraudster: Adversarial Attacks on Graph Neural Network Based Vertical Federated Learning | preprint | 2021 | [PDF] [Code] |
Leveraging a Federation of Knowledge Graphs to Improve Faceted Search in Digital Libraries kg. |
preprint | 2021 | [PDF] |
Federated Myopic Community Detection with One-shot Communication | preprint | 2021 | [PDF] |
Federated Graph Learning -- A Position Paper surv. |
preprint | 2021 | [PDF] |
A Vertical Federated Learning Framework for Graph Convolutional Network | preprint | 2021 | [PDF] |
FedGL: Federated Graph Learning Framework with Global Self-Supervision | preprint | 2021 | [PDF] |
FL-AGCNS: Federated Learning Framework for Automatic Graph Convolutional Network Search | preprint | 2021 | [PDF] |
Towards On-Device Federated Learning: A Direct Acyclic Graph-based Blockchain Approach | preprint | 2021 | [PDF] |
GraphFL: A Federated Learning Framework for Semi-Supervised Node Classification on Graphs | preprint | 2020 | [PDF] |
Improving Federated Relational Data Modeling via Basis Alignment and Weight Penalty kg. |
preprint | 2020 | [PDF] |
Federated Dynamic GNN with Secure Aggregation | preprint | 2020 | [PDF] |
GraphFederator: Federated Visual Analysis for Multi-party Graphs | preprint | 2020 | [PDF] |
Privacy-Preserving Graph Neural Network for Node Classification | preprint | 2020 | [PDF] |
Peer-to-peer federated learning on graphs | preprint | 2019 | [PDF] |
- [Arxiv 2021] Privacy-Preserving Graph Convolutional Networks for Text Classification. [PDF]
- [Arxiv 2021] GraphMI: Extracting Private Graph Data from Graph Neural Networks. [PDF]
- [Arxiv 2021] Towards Representation Identical Privacy-Preserving Graph Neural Network via Split Learning. [PDF]
- [Arxiv 2020] Locally Private Graph Neural Networks. [PDF]
This section refers to DBLP search engine.
Title | Venue | Year | Materials |
---|---|---|---|
Federated Random Forests can improve local performance of predictive models for various healthcare applications | Bioinform. | 2022 | [PUB.] [Code] |
Federated Forest | TBD | 2022 | [PDF] [PUB.] |
Federated Functional Gradient Boosting | AISTATS | 2022 | [PDF] [PUB.] [Code] |
Fed-GBM: a cost-effective federated gradient boosting tree for non-intrusive load monitoring | e-Energy | 2022 | [PUB.] |
eFL-Boost: Efficient Federated Learning for Gradient Boosting Decision Trees | IEEE Access | 2022 | [PUB.] |
Random Forest Based on Federated Learning for Intrusion Detection | AIAI | 2022 | [PUB.] |
Cross-silo federated learning based decision trees | SAC | 2022 | [PUB.] |
Leveraging Spanning Tree to Detect Colluding Attackers in Federated Learning | INFCOM Workshops | 2022 | [PUB.] |
VF2Boost: Very Fast Vertical Federated Gradient Boosting for Cross-Enterprise Learning | SIGMOD π | 2021 | [PUB.] |
An Efficiency-Boosting Client Selection Scheme for Federated Learning With Fairness Guarantee | TPDS π | 2021 | [PDF] [PUB.] |
A Blockchain-Based Federated Forest for SDN-Enabled In-Vehicle Network Intrusion Detection System | IEEE Access | 2021 | [PUB.] |
Research on privacy protection of multi source data based on improved gbdt federated ensemble method with different metrics | Phys. Commun. | 2021 | [PUB.] |
Fed-EINI: An Efficient and Interpretable Inference Framework for Decision Tree Ensembles in Vertical Federated Learning | IEEE BigData | 2021 | [PDF] [PUB.] |
Gradient Boosting Forest: a Two-Stage Ensemble Method Enabling Federated Learning of GBDTs | ICONIP | 2021 | [PUB.] |
A k-Anonymised Federated Learning Framework with Decision Trees | DPM/CBT @ESORICS | 2021 | [PUB.] |
AF-DNDF: Asynchronous Federated Learning of Deep Neural Decision Forests | SEAA | 2021 | [PUB.] |
Compression Boosts Differentially Private Federated Learning | EuroS&P | 2021 | [PDF] [PUB.] |
Practical Federated Gradient Boosting Decision Trees | AAAI π | 2020 | [PDF] [PUB.] [Code] |
Boosting Privately: Federated Extreme Gradient Boosting for Mobile Crowdsensing | ICDCS | 2020 | [PDF] [PUB.] |
FedCluster: Boosting the Convergence of Federated Learning via Cluster-Cycling | IEEE BigData | 2020 | [PDF] [PUB.] |
Bandwidth Slicing to Boost Federated Learning Over Passive Optical Networks | IEEE Communications Letters | 2020 | [PUB.] |
Privacy Preserving Vertical Federated Learning for Tree-based Models | Proc. VLDB Endow. | 2020 | [PDF] [PUB.] |
DFedForest: Decentralized Federated Forest | Blockchain | 2020 | [PUB.] |
Straggler Remission for Federated Learning via Decentralized Redundant Cayley Tree | LATINCOM | 2020 | [PUB.] |
Federated Soft Gradient Boosting Machine for Streaming Data | Federated Learning | 2020 | [PUB.] |
Federated Learning of Deep Neural Decision Forests | LOD | 2019 | [PUB.] |
FedGBF: An efficient vertical federated learning framework via gradient boosting and bagging | preprint | 2022 | [PDF] |
An Efficient and Robust System for Vertically Federated Random Forest | preprint | 2022 | [PDF] |
Guess what? You can boost Federated Learning for free | preprint | 2021 | [PDF] |
SecureBoost+ : A High Performance Gradient Boosting Tree Framework for Large Scale Vertical Federated Learning π₯ | preprint | 2021 | [PDF] [Code] |
Fed-TGAN: Federated Learning Framework for Synthesizing Tabular Data | preprint | 2021 | [PDF] |
A Tree-based Federated Learning Approach for Personalized Treatment Effect Estimation from Heterogeneous Data Sources | preprint | 2021 | [PDF] [Code] |
Adaptive Histogram-Based Gradient Boosted Trees for Federated Learning | preprint | 2020 | [PDF] |
FederBoost: Private Federated Learning for GBDT | preprint | 2020 | [PDF] |
Privacy Preserving Text Recognition with Gradient-Boosting for Federated Learning | preprint | 2020 | [PDF] [Code] |
Cloud-based Federated Boosting for Mobile Crowdsensing | preprint | 2020 | [arxiv] |
Federated Extra-Trees with Privacy Preserving | preprint | 2020 | [PDF] |
Bandwidth Slicing to Boost Federated Learning in Edge Computing | preprint | 2019 | [PDF] |
Revocable Federated Learning: A Benchmark of Federated Forest | preprint | 2019 | [PDF] |
List of papers in the field of federated learning in Nature(and its sub-journals), Cell, Science(and Science Advances) and PANS refers to WOS search engine.
Title | Venue | Year | Materials |
---|---|---|---|
Shifting machine learning for healthcare from development to deployment and from models to data | Nat. Biomed. Eng | 2022 | [PUB.] |
Communication-efficient federated learning via knowledge distillation | Nat Commun | 2022 | [PUB.] |
A federated graph neural network framework for privacy-preserving personalization | Nat Commun | 2022 | [PUB.] [Code] |
Swarm Learning for decentralized and confidential clinical machine learning | Nature π | 2021 | [PUB.] |
Adversarial interference and its mitigations in privacy-preserving collaborative machine learning | Nat. Mach. Intell. | 2021 | [PUB.] |
End-to-end privacy preserving deep learning on multi-institutional medical imaging | Nat. Mach. Intell. | 2021 | [PUB.] |
Federated learning for predicting clinical outcomes in patients with COVID-19 | Nat Med | 2021 | [PUB.] |
Communication-efficient federated learning | PANS | 2021 | [PUB.] [Code] |
Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence | Nat. Mach. Intell. | 2021 | [PUB.] |
Secure, privacy-preserving and federated machine learning in medical imaging | Nat Mach Intell | 2020 | [PUB.] |
Breaking medical data sharing boundaries by using synthesized radiographs | Science Advances | 2020 | [PUB.] |
(todo)
More items will be added to the repository. Please feel free to suggest other key resources by opening an issue report, submitting a pull request, or dropping me an email @ (im.young@foxmail.com). Enjoy reading!
Many thanks β€οΈ to the other awesome list: