Privacy-Preserving Federated Learning

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41 papers7 papers in the last four weeks, up 40% on the four weeks before. 0.0% of all new papers.

  1. Secure and Privacy-Preserving Vertical Federated Learning

    Apr 15, 2026Shan Jin, Sai Rahul Rachuri, Yizhen Wang +2Privacy-Preserving Federated LearningFederated Learning

    Visa Research

  2. PrivEraserVerify: Efficient, Private, and Verifiable Federated Unlearning

    Apr 14, 2026Parthaw Goswami, Md Khairul Islam, Ashfak YeafiFederated UnlearningPrivacy-Preserving Federated Learning

    Department of Electronics and Communication Engineering, Khulna University of Engineering & Technology, Khulna-9203, Bangladesh · Department of Mathematics and Computer Science, Hobart and William Smith Colleges, Geneva, NY, USA · Department of Electrical and Electronic Engineering, Khulna University of Engineering & Technology, Khulna-9203, Bangladesh

  3. Scalable and Private Federated Learning Using Distributed Differential Privacy and Secure Aggregation

    Apr 8, 2026Wenjing Wei, Farid Nait-Abdesselam, Alla JamminePrivacy-Preserving Federated LearningDifferentially Private Federated Learning

    Université Paris Cité, Paris, France

  4. FedFG: Privacy-Preserving and Robust Federated Learning via Flow-Matching Generation

    Mar 30, 2026Ruiyang Wang, Rong Pan, Zhengan YaoPrivacy-Preserving Federated LearningFederated Learning

    School of Mathematics, Sun Yat-sen University, Guangzhou 510275, China · School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou 510006, China · Institute of Advanced Studies Hong Kong, Sun Yat-sen University, Hong Kong

  5. PTOPOFL: Topology-Guided Personalised Federated Learning with Persistent-Homology Client Descriptors

    Mar 4, 2026Kelly L Vomo-Donfack, Adryel Hoszu, Grégory Ginot +1Privacy-Preserving Federated LearningFederated Learning

    Université Sorbonne Paris Nord, LAGA, CNRS, UMR 7539, Laboratoire d’excellence Infibrex, F-93430 Villetaneuse, France · Instituto de Hortofruticultura Subtropical y Mediterránea La Mayora (IHSM), Universidad de Málaga–Consejo Superior de Investigaciones Científicas, Málaga, Spain

  6. Zero-Knowledge Federated Learning with Lattice-Based Hybrid Encryption for Quantum-Resilient Medical AI

    Mar 3, 2026Edouard LansiauxQuantum Federated LearningPrivacy-Preserving Federated Learning

    Department of Emergency Medicine & STaR-AI Research Group, CHU de Lille, Université de Lille, Lille, France

  7. Private and Robust Contribution Evaluation in Federated Learning

    Feb 25, 2026Delio Jaramillo Velez, Gergely Biczok, Alexandre Graell i Amat +2Federated LearningPrivacy-Preserving ML

    University of La Laguna Tenerife, Spain · HUN-REN Hungarian Research Network Budapest, Hungary · Chalmers University Gotheburg, Sweden +2

  8. Federated Learning-Assisted Optimization of Mobile Transmission with Digital Twins

    Feb 20, 2026Mohammad Heydari, Terence D. Todd, Dongmei Zhao +1Privacy-Preserving Federated LearningWireless Resource Allocation

    Department of Electrical and Computer Engineering, McMaster University, CANADA · Department of Computing and Software, McMaster University, CANADA

  9. ERIS: Enhancing the Privacy-Utility-Scalability Trade-Off in Federated Learning via Federated Shard Aggregation

    Feb 9, 2026Dario Fenoglio, Pasquale Polverino, Akash Dhasade +3Federated LearningFederated Learning Aggregation

    Universit`a della Svizzera italiana Lugano, Switzerland · Carnegie Mellon University Pittsburgh, PA, United States

  10. ELSA: Efficient LLM-Centric Split Aggregation for Privacy-Aware Hierarchical Federated Learning over the Network Edge

    Jan 20, 2026Xiaohong Yang, Tong Xie, Minghui Liwang +6Federated Fine-TuningFederated Learning

    the School of Informatics, Xiamen University, Fujian, China · the National University of Singapore · the Department of Control Science and Engineering, the National Key Laboratory of Autonomous Intelligent Unmanned Systems, and also with Frontiers Science Center for Intelligent Autonomous Systems, Ministry of Education, Tongji University, Shanghai, China +2

  11. A Privacy-Preserving Federated Learning Method for Heterogeneous Clients

    Nov 8, 2025Yusaku Negoya, Feifei Cui, Zilong Zhang +3Privacy-Preserving Federated LearningDifferentially Private Federated Learning

    Department of Computer and Network Engineering, The University of Electro-Communications, Tokyo, Japan · School of Computer Science and Technology, Hainan University, Haikou 570228, China. · Department of Electrical and Computer Engineering, University of Houston, Houston, TX, 77204, USA +1