VAFL: a Method of Vertical Asynchronous Federated Learning
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Abstract (arXiv)
Horizontal Federated learning (FL) handles multi-client data that share the same set of features, and vertical FL trains a better predictor that combine all the features from different clients. This paper targets solving vertical FL in an asynchronous fashion, and develops a simple FL method. The new method allows each client to run stochastic gradient algorithms without coordination with other clients, so it is suitable for intermittent connectivity of clients. This method further uses a new technique of perturbed local embedding to ensure data privacy and improve communication efficiency. Theoretically, we present the convergence rate and privacy level of our method for strongly convex, nonconvex and even nonsmooth objectives separately. Empirically, we apply our method to FL on various image and healthcare datasets. The results compare favorably to centralized and synchronous FL methods.
Key facts. Cited by 87 papers in the map (data through 7 Oct 2026). First posted on arXiv 12 Jul 2020.
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Citing papers per year: 2021: 14; 2022: 19; 2023: 20; 2024: 16; 2025: 13; 2026: 5.
87 papers.
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- 2021Federated Learning on Non-IID Data: A Surveycited by 345
- 2023Heterogeneous Federated Learning: State-of-the-art and Research Challengescited by 160
- 2022Vertical Federated Learning: Concepts, Advances and Challengescited by 104
- 2021CAFE: Catastrophic Data Leakage in Vertical Federated Learningcited by 76
- 2022A Survey on Heterogeneous Federated Learningcited by 42
- 2023Momentum Benefits Non-IID Federated Learning Simply and Provablycited by 37
- 2022Compressed-VFL: Communication-Efficient Learning with Vertically Partitioned Datacited by 36
- 2022Federated Learning for Medical Applications: A Taxonomy, Current Trends, Challenges, and Future Research Directionscited by 34
- 2021FedV: Privacy-Preserving Federated Learning over Vertically Partitioned Datacited by 31
- 2023A Survey on Vertical Federated Learning: From a Layered Perspectivecited by 30
- 2022AFLGuard: Byzantine-robust Asynchronous Federated Learningcited by 29
- 2022Differentially Private Label Protection in Split Learningcited by 25
38 more
- 2024Asynchronous Federated Reinforcement Learning with Policy Gradient Updates: Algorithm Design and Convergence Analysiscited by 21
- 2021Vertical Federated Learning without Revealing Intersection Membershipcited by 19
- 2022Practical Vertical Federated Learning with Unsupervised Representation Learningcited by 19
- 2022Fair and efficient contribution valuation for vertical federated learningcited by 18
- 2022Vertical Federated Learning: A Structured Literature Reviewcited by 17
- 2023FedVS: Straggler-Resilient and Privacy-Preserving Vertical Federated Learning for Split Modelscited by 17
- 2022Towards Communication-efficient Vertical Federated Learning Training via Cache-enabled Local Updatescited by 15
- 2023FedSDG-FS: Efficient and Secure Feature Selection for Vertical Federated Learningcited by 15
- 2022Combined Federated and Split Learning in Edge Computing for Ubiquitous Intelligence in Internet of Things: State of the Art and Future Directionscited by 14
- 2022Coresets for Vertical Federated Learning: Regularized Linear Regression and K-Means Clusteringcited by 14
- 2024Vertical Federated Learning for Effectiveness, Security, Applicability: A Surveycited by 14
- 2022Vertical Semi-Federated Learning for Efficient Online Advertisingcited by 12
- 2024Advances in Robust Federated Learning: A Survey with Heterogeneity Considerationscited by 12
- 2022Improving Privacy-Preserving Vertical Federated Learning by Efficient Communication with ADMMcited by 10
- 2022Differentially Private Vertical Federated Clusteringcited by 10
- 2024FADAS: Towards Federated Adaptive Asynchronous Optimizationcited by 10
- 2022Desirable Companion for Vertical Federated Learning: New Zeroth-Order Gradient Based Algorithmcited by 9
- 2021A Federated Data-Driven Evolutionary Algorithmcited by 8
- 2021GAL: Gradient Assisted Learning for Decentralized Multi-Organization Collaborationscited by 8
- 2021Achieving Model Fairness in Vertical Federated Learningcited by 8
- 2023Vertical Federated Learning: Taxonomies, Threats, and Prospectscited by 8
- 2023Federated Learning of Models Pre-Trained on Different Features with Consensus Graphscited by 8
- 2021Multi-Tier Federated Learning for Vertically Partitioned Datacited by 7
- 2023Label Inference Attack against Split Learning under Regression Settingcited by 7
- 2023Robust and IP-Protecting Vertical Federated Learning against Unexpected Quitting of Partiescited by 7
- 2024A Survey of Privacy Threats and Defense in Vertical Federated Learning: From Model Life Cycle Perspectivecited by 7
- 2021Cross-Silo Federated Learning for Multi-Tier Networks with Vertical and Horizontal Data Partitioningcited by 6
- 2023Online Vertical Federated Learning for Cooperative Spectrum Sensingcited by 6
- 2024A Survey on Contribution Evaluation in Vertical Federated Learningcited by 5
- 2021A Vertical Federated Learning Framework for Horizontally Partitioned Labelscited by 4
- 2022Differentially Private Vertical Federated Learningcited by 4
- 2023Secure Vertical Federated Learning Under Unreliable Connectivitycited by 4
- 2025Vertical Federated Learning in Practice: The Good, the Bad, and the Uglycited by 4
- 2021Sample-based and Feature-based Federated Learning for Unconstrained and Constrained Nonconvex Optimization via Mini-batch SSCAcited by 3
- 2021Multi-Party Dual Learningcited by 3
- 2023GLASU: A Communication-Efficient Algorithm for Federated Learning with Vertically Distributed Graph Datacited by 3
- 2023Efficient Vertical Federated Learning with Secure Aggregationcited by 3
- 2024URVFL: Undetectable Data Reconstruction Attack on Vertical Federated Learningcited by 3
50 most cited of 87 All 87 (JSON)
- 2026Optimizing Server Placement for Vertical Federated Learning in Dynamic Edge/Fog Networks10 May 2026
- 2026Scalable and Private Federated Learning Using Distributed Differential Privacy and Secure Aggregation8 Apr 2026
- 2026SecureAFL: Secure Asynchronous Federated Learning4 Apr 2026
- 2026Revisiting Gradient Staleness: Evaluating Distance Metrics for Asynchronous Federated Learning Aggregation9 Mar 2026
- 2026Learning Unknown Interdependencies for Decentralized Root Cause Analysis in Nonlinear Dynamical Systems25 Feb 2026
- 2025Certifying the Right to Be Forgotten: Primal-Dual Optimization for Sample and Label Unlearning in Vertical Federated Learning29 Dec 2025
- 2025The Sherpa.ai Blind Vertical Federated Learning Paradigm to Minimize the Number of Communications19 Oct 2025
- 2025BlendFL: Blended Federated Learning for Handling Multimodal Data Heterogeneity15 Oct 2025
- 2025PubSub-VFL: Towards Efficient Two-Party Split Learning in Heterogeneous Environments via Publisher/Subscriber Architecture14 Oct 2025
- 2025FedOne: Query-Efficient Federated Learning for Black-box Discrete Prompt Learning17 Jun 2025
- 2025Event-Driven Online Vertical Federated Learning17 Jun 2025
- 2025ICAFS: Inter-Client-Aware Feature Selection for Vertical Federated Learning15 Apr 2025
38 more
- 2025Tree-based Models for Vertical Federated Learning: A Survey3 Apr 2025
- 2025Scaling Probabilistic Circuits via Data Partitioning11 Mar 2025
- 2025Communication-Efficient and Differentially Private Vertical Federated Learning with Zeroth-Order Optimization27 Feb 2025
- 2025Vertical Federated Learning in Practice: The Good, the Bad, and the Ugly12 Feb 2025
- 2025Federated Granger Causality Learning for Interdependent Clients with State Space Representation23 Jan 2025
- 2025Cooperative Decentralized Backdoor Attacks on Vertical Federated Learning16 Jan 2025
- 2024One Node Per User: Node-Level Federated Learning for Graph Neural Networks29 Sep 2024
- 2024Contrastive Federated Learning with Tabular Data Silos10 Sep 2024
- 2024Active-Passive Federated Learning for Vertically Partitioned Multi-view Data6 Sep 2024
- 2024FADAS: Towards Federated Adaptive Asynchronous Optimization25 Jul 2024
- 2024Communication-efficient Vertical Federated Learning via Compressed Error Feedback20 Jun 2024
- 2024Share Secrets for Privacy: Confidential Forecasting with Vertical Federated Learning31 May 2024
- 2024Vertical Federated Learning for Effectiveness, Security, Applicability: A Survey25 May 2024
- 2024Asynchronous Federated Stochastic Optimization for Heterogeneous Objectives Under Arbitrary Delays16 May 2024
- 2024Advances in Robust Federated Learning: A Survey with Heterogeneity Considerations16 May 2024
- 2024A Survey on Contribution Evaluation in Vertical Federated Learning3 May 2024
- 2024URVFL: Undetectable Data Reconstruction Attack on Vertical Federated Learning30 Apr 2024
- 2024Asynchronous Federated Reinforcement Learning with Policy Gradient Updates: Algorithm Design and Convergence Analysis9 Apr 2024
- 2024TablePuppet: A Generic Framework for Relational Federated Learning23 Mar 2024
- 2024AFGI: Towards Accurate and Fast-convergent Gradient Inversion Attack in Federated Learning13 Mar 2024
- 2024Decoupled Vertical Federated Learning for Practical Training on Vertically Partitioned Data6 Mar 2024
- 2024A Survey of Privacy Threats and Defense in Vertical Federated Learning: From Model Life Cycle Perspective6 Feb 2024
- 2023Robust Collaborative Inference with Vertically Split Data Over Dynamic Device Environments27 Dec 2023
- 2023Online Vertical Federated Learning for Cooperative Spectrum Sensing18 Dec 2023
- 2023Task-Oriented Edge Networks: Decentralized Learning Over Wireless Fronthaul3 Dec 2023
- 2023Privacy-preserving design of graph neural networks with applications to vertical federated learning31 Oct 2023
- 2023A Multi-Token Coordinate Descent Method for Semi-Decentralized Vertical Federated Learning18 Sep 2023
- 2023Flexible Differentially Private Vertical Federated Learning with Adaptive Feature Embeddings26 Jul 2023
- 2023Heterogeneous Federated Learning: State-of-the-art and Research Challenges20 Jul 2023
- 2023Momentum Benefits Non-IID Federated Learning Simply and Provably28 Jun 2023
- 2023Secure and Fast Asynchronous Vertical Federated Learning via Cascaded Hybrid Optimization28 Jun 2023
- 2023Federated Learning of Models Pre-Trained on Different Features with Consensus Graphs2 Jun 2023
- 2023Secure Vertical Federated Learning Under Unreliable Connectivity26 May 2023
- 2023Efficient Vertical Federated Learning with Secure Aggregation18 May 2023
- 2023FedVS: Straggler-Resilient and Privacy-Preserving Vertical Federated Learning for Split Models26 Apr 2023
- 2023A Survey on Vertical Federated Learning: From a Layered Perspective4 Apr 2023
- 2023Robust and IP-Protecting Vertical Federated Learning against Unexpected Quitting of Parties28 Mar 2023
- 2023FedAgg: Adaptive Federated Learning with Aggregated Gradients28 Mar 2023
50 newest of 87 All 87 (JSON)
- 2021Federated Learning on Non-IID Data: A Surveycited by 345
- 2023Heterogeneous Federated Learning: State-of-the-art and Research Challengescited by 160
- 2022Vertical Federated Learning: Concepts, Advances and Challengescited by 104
- 2021CAFE: Catastrophic Data Leakage in Vertical Federated Learningcited by 76
- 2022A Survey on Heterogeneous Federated Learningcited by 42
- 2023Momentum Benefits Non-IID Federated Learning Simply and Provablycited by 37
- 2022Compressed-VFL: Communication-Efficient Learning with Vertically Partitioned Datacited by 36
- 2022Federated Learning for Medical Applications: A Taxonomy, Current Trends, Challenges, and Future Research Directionscited by 34
- 2021FedV: Privacy-Preserving Federated Learning over Vertically Partitioned Datacited by 31
- 2023A Survey on Vertical Federated Learning: From a Layered Perspectivecited by 30
- 2022AFLGuard: Byzantine-robust Asynchronous Federated Learningcited by 29
- 2022Differentially Private Label Protection in Split Learningcited by 25
12 most cited of 86 All 86 (JSON)
- 2026Optimizing Server Placement for Vertical Federated Learning in Dynamic Edge/Fog Networks10 May 2026
- 2026Scalable and Private Federated Learning Using Distributed Differential Privacy and Secure Aggregation8 Apr 2026
- 2026SecureAFL: Secure Asynchronous Federated Learning4 Apr 2026
- 2026Revisiting Gradient Staleness: Evaluating Distance Metrics for Asynchronous Federated Learning Aggregation9 Mar 2026
- 2026Learning Unknown Interdependencies for Decentralized Root Cause Analysis in Nonlinear Dynamical Systems25 Feb 2026
- 2025The Sherpa.ai Blind Vertical Federated Learning Paradigm to Minimize the Number of Communications19 Oct 2025
- 2025BlendFL: Blended Federated Learning for Handling Multimodal Data Heterogeneity15 Oct 2025
- 2025PubSub-VFL: Towards Efficient Two-Party Split Learning in Heterogeneous Environments via Publisher/Subscriber Architecture14 Oct 2025
- 2025FedOne: Query-Efficient Federated Learning for Black-box Discrete Prompt Learning17 Jun 2025
- 2025Event-Driven Online Vertical Federated Learning17 Jun 2025
- 2025ICAFS: Inter-Client-Aware Feature Selection for Vertical Federated Learning15 Apr 2025
- 2025Tree-based Models for Vertical Federated Learning: A Survey3 Apr 2025
12 newest of 86 All 86 (JSON)