Federated-Learning-on-Graph-and-Tabular-Data

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Table of Contents

• Papers
  • FL on Graph Data and Graph Neural Networks
  • FL on Tabular Data
• Framework
• Datasets

Papers

keywords

Statistics: 🔥 code is available & stars >= 1000 | ⭐ citation >= 50 | 🎓 Top-tier venue

kg.: Knowledge Graph | data.: dataset  |   surv.: survey

Update log

Last updated: 2022/06/14

• 2022/05/25 - complete the paper and code lists of FL on tabular data and Tree algorithms

• 2022/05/25 - add the paper list of FL on tabular data and Tree algorithms

• 2022/05/24 - complete the paper and code lists of FL on graph data and Graph Neural Networks

• 2022/05/23 - add the paper list of FL on graph data and Graph Neural Networks

• 2022/05/21 - update all of Federated Learning Framework

FL on Graph Data and Graph Neural Networks

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
Meta-Learning Based Knowledge Extrapolation for Knowledge Graphs in the Federated Setting kg.	IJCAI 🎓	2022	[PDF] [Code]
Efficient Federated Learning on Knowledge Graphs via Privacy-preserving Relation Embedding Aggregation kg.	ACL Workshop	2022	[PDF] [Code]
SpreadGNN: Serverless Multi-task Federated Learning for Graph Neural Networks	AAAI 🎓	2022	[PDF] [Code]
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 🎓	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 🎓	2021	[PDF] [PUB.]
Cross-Node Federated Graph Neural Network for Spatio-Temporal Data Modeling	KDD 🎓	2021	[PDF] [Code]
FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks 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 🎓	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]
SGNN: A Graph Neural Network Based Federated Learning Approach by Hiding Structure	BigData	2019	[PDF] [PUB.]
FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient Package for Federated Graph Learning	preprint	2022	[PDF] [Code]
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]
Power Allocation for Wireless Federated Learning using Graph Neural Networks	preprint	2021	[PDF] [Code]
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]
FedGNN: Federated Graph Neural Network for Privacy-Preserving Recommendation	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]

Private Graph Neural Networks (todo)

• [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]

FL on Tabular Data

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 Functional Gradient Boosting	AISTATS	2022	[PDF] [PUB.] [Code]
eFL-Boost: Efficient Federated Learning for Gradient Boosting Decision Trees	IEEE Access	2022	[PUB.]
Federated Forest	TBD	2022	[PDF] [PUB.]
Cross-silo federated learning based decision trees	SAC	2022	[PUB.]
VF2Boost: Very Fast Vertical Federated Gradient Boosting for Cross-Enterprise Learning	SIGMOD 🎓	2021	[PUB.]
An Efficiency-Boosting Client Selection Scheme for Federated Learning With Fairness Guarantee	TPDS 🎓	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 🎓	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	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]

Framework

Federated Learning Framework

Platform	Papers	Affiliations	Graph data and algorithms	Tabular data and algorithms	Materials
PySyft	A generic framework for privacy preserving deep learning	OpenMined			Doc
FATE	FATE: An Industrial Grade Platform for Collaborative Learning With Data Protection	WeBank		✅✅	Doc Doc(zh)
MindSpore Federated		HUAWEI			Doc Homepage
TFF(Tensorflow-Federated)	Towards Federated Learning at Scale: System Design	Google			Doc Homepage
FedML	FedML: A Research Library and Benchmark for Federated Machine Learning	FedML	✅✅	✅	Doc
Flower	Flower: A Friendly Federated Learning Research Framework	flower.dev adap			Doc
Fedlearner		Bytedance
FederatedScope	FederatedScope: A Flexible Federated Learning Platform for Heterogeneity	Alibaba DAMO Academy	✅✅		Doc Homepage
LEAF	LEAF: A Benchmark for Federated Settings	CMU
Rosetta		matrixelements			Doc Homepage
PaddleFL		Baidu			Doc
OpenFL	OpenFL: An open-source framework for Federated Learning	Intel			Doc
IBM Federated Learning	IBM Federated Learning: an Enterprise Framework White Paper	IBM		✅	Papers
Fedlab	FedLab: A Flexible Federated Learning Framework	SMILELab			Doc Doc(zh) Homepage
FedScale	FedScale: Benchmarking Model and System Performance of Federated Learning at Scale	fedscale.ai
plato		UofT
FLSim		facebook research
PyVertical	PyVertical: A Vertical Federated Learning Framework for Multi-headed SplitNN	OpenMined
9nfl		JD
msrflute	FLUTE: A Scalable, Extensible Framework for High-Performance Federated Learning Simulations	microsoft			Doc
FedLearn	Fedlearn-Algo: A flexible open-source privacy-preserving machine learning platform	JD
FEDn	Scalable federated machine learning with FEDn	scaleoutsystems			Doc
EasyFL	EasyFL: A Low-code Federated Learning Platform For Dummies	NTU
OpenFed	OpenFed: A Comprehensive and Versatile Open-Source Federated Learning Framework				Doc
FedEval	FedEval: A Benchmark System with a Comprehensive Evaluation Model for Federated Learning	HKU			Doc
Flame		Cisco
APPFL					Doc
Clara		NVIDIA

Datasets

(todo)

How to contact us

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!

Acknowledgments

Many thanks ❤️ to the other awesome list:

• Federated Learning

  • Awesome-Federated-Learning-on-Graph-and-GNN-papers
  • Awesome-Federated-Machine-Learning
  • Awesome-Federated-Learning
  • awesome-federated-learning
  • Federated-Learning
  • FLsystem-paper

• Other fields

  • anomaly-detection-resources
  • awesome-image-registration