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| When: Nov 4, 2025 - Nov 8, 2025 Submission Deadline: Jul 25, 2025 | ||
| Workshop FLEdge-AI @ ACM MOBICOM 2025 • Organizers and Chairs • Francesco Piccialli (University of Naples Federico II, Italy) • David Camacho (Universidad Politécnica de Madrid, Sp... | ||
| FEDERATED LEARNING MACHINE LEARNING EDGE COMPUTING EDGE AI | ||
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| When: Sep 1, 2025 - Sep 4, 2025 Submission Deadline: Jul 1, 2025 | ||
| Call for Papers (CFP) • AI-IoT 2025 – The 1st International Workshop on AI-Driven Smart IoT: Innovations, Challenges & Future Directions • Co-located with Cyber-AI 2025 • 1–4 Se... | ||
| IOT FEDERATED LEARNING AI CYBER PHYSICAL SYSTEM | ||
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| When: Jun 5, 2024 - Jun 6, 2024 Submission Deadline: Mar 15, 2024 | ||
| Following a data protection by design principle, federated learning has emerged as a more privacy-friendly machine learning paradigm for independent actors to collaboratively train a machine learning... | ||
| PRIVACY MACHINE LEARNING FEDERATED LEARNING APPLICATIONS | ||
FL@FM-ICME 2024 : International Workshop on Federated Learning and Foundation Models for Multi-MediaNiagara Falls, ON, Canada |
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| When: Jul 15, 2024 - Jul 19, 2024 Submission Deadline: Mar 23, 2024 | ||
| [Call for Papers] • Foundation models (FMs) are typically associated with large language models (LLMs), like ChatGPT, and are characterized by their scale and broad applicability. While these m... | ||
| ARTIFICIAL INTELLIGENCE MACHINE LEARNING FEDERATED LEARNING FOUNDATION MODELS | ||
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| When: Dec 18, 2024 - Dec 20, 2024 Submission Deadline: Jul 31, 2024 | ||
| ICMLA 2024 aims to bring together researchers and practitioners to present their latest achievements and innovations in the area of machine learning (ML). • The conference provides a leading in... | ||
| MACHINE LEARNING BAYESIAN NETWORKS FEDERATED LEARNING NEURAL NETWORKS | ||
FL-ICME 2024 : ICME'24 Special Session on Trustworthy Federated Learning for MultimediaNiagara Falls, ON, Canada |
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| When: Jul 15, 2024 - Jul 19, 2024 Submission Deadline: Dec 30, 2023 | ||
| As artificial intelligence (AI) research advances, the key obstacle to widespread AI adoption has shifted from technical challenges to gaining stakeholders' trust. Building AI techniques that are fai... | ||
| ARTIFICIAL INTELLIGENCE MACHINE LEARNING FEDERATED LEARNING FOUNDATION MODELS | ||
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| When: Jun 30, 2024 - Jul 5, 2024 Submission Deadline: Jan 15, 2024 | ||
| Federated Learning (FL) is an emerging machine learning paradigm that allows multiple end-users to collaboratively train models without sharing their private data. Existing FL frameworks are undergoi... | ||
| ARTIFICIAL INTELLIGENCE MACHINE LEARNING FEDERATED LEARNING FOUNDATION MODELS | ||
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| When: May 14, 2024 - May 14, 2024 Submission Deadline: Feb 5, 2024 | ||
| [Call for Papers] • Foundation models (FMs) are typically associated with large language models (LLMs), like ChatGPT, and are characterized by their scale and broad applicability. While these m... | ||
| ARTIFICIAL INTELLIGENCE MACHINE LEARNING FEDERATED LEARNING FOUNDATION MODELS | ||
FLEDGE 2024 : Federated Learning on the EdgeStanford, CA |
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| When: Mar 25, 2024 - Mar 27, 2024 Submission Deadline: Jan 12, 2024 | ||
| Computational intelligence bears the prospect of a trendsetting technology able to unlock solutions to previously difficult and large-scale problems outside of the current cloud-centric paradigm. In ... | ||
| FEDERATED LEARNING EDGE AI DISTRIBUTED LEARNING DISTRIBUTED NETWORKS | ||
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| When: Dec 16, 2023 - Dec 16, 2023 Submission Deadline: Oct 2, 2023 | ||
| [Call for Papers] • Training machine learning models in a centralized fashion often faces significant challenges due to regulatory and privacy concerns in real-world use cases. These include di... | ||
| ARTIFICIAL INTELLIGENCE MACHINE LEARNING FEDERATED LEARNING FOUNDATION MODELS | ||
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| When: Sep 11, 2023 - Sep 15, 2023 Submission Deadline: Jun 30, 2023 | ||
| --- Call for papers - Apologies for multiple posting --- • 1st Workshop on Federated Learning in Medical Imaging and Vision • Held in conjunction with the “22nd International Conference... | ||
| ARTIFICIAL INTELLIGENCE FEDERATED LEARNING MEDICAL IMAGING | ||
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| Submission Deadline: Oct 20, 2023 | ||
| Computer Networks – SI on Computing Continuum and Federated Learning for Smart Cities – Call for Papers • https://www.sciencedirect.com/journal/computer-networks/about/call-for-papers#compu... | ||
| MACHINE LEARNING ARTIFICIAL INTELLIGENCE COMPUTING CONTINUUM SMART CITY | ||
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| When: Aug 6, 2023 - Aug 10, 2023 Submission Deadline: May 30, 2023 | ||
| By hosting this workshop at SIGKDD, we hope to promote the development of federated learning as a scientific field and encourage data mining researchers and practitioners to collaborate on this impor... | ||
| DATA MINING FEDERATED LEARNING DISTRIBUTED LEARNING MACHINE LEARNING | ||
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| When: Sep 18, 2023 - Sep 20, 2023 Submission Deadline: Jul 15, 2023 | ||
| About • We live in a data-driven era where AI and ML are integrated into every aspect of life and industry when making decisions. Recent AI/ML applications, scenarios, and use cases data source... | ||
| FEDERATED LEARNING BIG DATA COMPUTING EDGE COMPUTING ML | ||
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| When: Dec 12, 2022 - Dec 15, 2022 Submission Deadline: Jul 10, 2022 | ||
| FMEC 2022 CFP: • Cloud computing provides large range of services and virtually unlimited available resources for users. New applications, such as virtual reality and smart building control, ha... | ||
| MOBILE EDGE COMPUTING FEDERATED LEARNING ARTIFICIAL INTELLIGENCE DATA PRIVACY AND SECURITY | ||
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| When: Sep 7, 2022 - Sep 9, 2022 Submission Deadline: May 18, 2022 | ||
| ===================================================================================== • KES-2022-IS18: Federated Learning: Advances and Open Challenges in Distributed and Cooperative Learning M... | ||
| COMPUTER SCIENCE FEDERATED LEARNING COOPERATIVE NN INTERNET OF THINGS | ||
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| Submission Deadline: Sep 30, 2022 | ||
| Special Issue on Federated and Transfer Learning Applications, Applied Sciences, MDPI • The classic example of machine learning is based on isolated learning—a single model for each task usin... | ||
| FEDERATED LEARNING TRANSFER LEARNING ARTIFICIAL INTELLIGENCE PRIVACY | ||
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| When: Apr 27, 2022 - Apr 27, 2022 Submission Deadline: Mar 24, 2022 | ||
| ================================================================================ • CALL FOR CONTRIBUTIONS • Thematic Session on • "Collaborative Machine Learning across IoT, Edge, F... | ||
| MACHINE LEARNING DISTRIBUTED SYSTEMS FEDERATED LEARNING EDGE/FOG/CLOUD | ||
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| When: Jul 23, 2022 - Jul 25, 2022 Submission Deadline: May 23, 2022 | ||
| [Call for Papers] • Federated Learning (FL), a learning paradigm that enables collaborative training of machine learning models in which data reside and remain in distributed data silos during ... | ||
| ARTIFICIAL INTELLIGENCE MACHINE LEARNING FEDERATED LEARNING TRUSTWORTHY COMPUTING | ||
CBMS Special Track 2022 : Federated Learning for Medical DataShenzhen, China (or virtual attendance) |
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| When: Jul 21, 2022 - Jul 23, 2022 Submission Deadline: Apr 25, 2022 | ||
| ====================================================================== • CBMS Special Track - Federated Learning for Medical Data • CALL FOR PAPERS • 21-23 July 2022 • Shenzhe... | ||
| FEDERATED LEARNING MEDICAL DATA | ||
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| When: Oct 20, 2022 - Oct 23, 2022 Submission Deadline: Jun 15, 2022 | ||
| Call-for-Papers • Emerging Information Processing and Management Paradigms: Edge Intelligence, Federated Learning, and Blockchain (VSI: IPMC2022 EMERGING) • A Special Issue for Informatio... | ||
| EDGE INTELLIGENCE FEDERATED LEARNING BLOCKCHAIN INFORMATION PROCESSING | ||
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| When: Jul 18, 2022 - Jul 23, 2022 Submission Deadline: Jan 31, 2022 | ||
| Special Session Abstract: • Federated Learning (FL) comes to rescue from standard centralized training of machine learning models, that is unfeasible in many interesting use-cases, where the as... | ||
| NEURAL NETWORKS FEDERATED LEARNING COOPERATIVE NEURAL NETWORKS DISTRIBUTED DEEP LEARNING | ||
FLSys 2020 : Federated Learning Systems: Towards Next-generation AISpringer-Studies in CI |
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| When: Dec 31, 2020 - Dec 31, 2020 Submission Deadline: Aug 31, 2020 | ||
| This book aims at congregating researchers and practitioners to share their research in showing how federated learning can transform next-generation artificial intelligence applications, and propose s... | ||
| ARTIFICIAL INTELLIGENCE DEEP LEARNING PRIVACY COMMUNICATION | ||
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| When: Jul 17, 2020 - Jul 18, 2020 Submission Deadline: May 17, 2020 | ||
| Training machine learning models in a centralized fashion often faces significant challenges due to regulatory and privacy concerns in real-world use cases. These include distributed training data, co... | ||
| ARTIFICIAL INTELLIGENCE MACHINE LEARNING DATA PRIVACY | ||
FL-IJCAI'20 : International Workshop on Federated Learning for User Privacy and Data Confidentiality in Conjunction with IJCAI 2020Pacifico Yokohama, Yokohama, Japan |
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| When: Jul 13, 2020 - Jul 13, 2020 Submission Deadline: Apr 26, 2020 | ||
| Privacy and security are becoming a key concern in our digital age. Companies and organizations are collecting a wealth of data on a daily basis. Data owners have to be very cautious while exploiting ... | ||
| ARTIFICIAL INTELLIGENCE MACHINE LEARNING | ||
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| When: Dec 13, 2019 - Dec 14, 2019 Submission Deadline: Sep 9, 2019 | ||
| Overview • Privacy and security are becoming major concerns in recent years, particularly as companies and organizations are collecting increasingly detailed information about their products and... | ||
| MACHINE LEARNING ARTIFICIAL INTELLIGENCE FEDERATED LEARNING DATA PRIVACY | ||
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| When: Dec 9, 2019 - Dec 12, 2019 Submission Deadline: Sep 15, 2019 | ||
| Introduction • Privacy and security are becoming a key concern in our digital age. Companies and organizations are collecting a wealth of data on a daily basis. Data owners have to be very cauti... | ||
| MACHINE LEARNING ARTIFICIAL INTELLIGENCE FEDERATED LEARNING BIG DATA | ||
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| When: Aug 12, 2019 - Aug 12, 2019 Submission Deadline: May 26, 2019 | ||
| Privacy and security are becoming a key concern in our digital age. Companies and organizations are collecting a wealth of data on a daily basis. Data owners have to be very cautious while unlocking t... | ||
| MACHINE LEARNING ARTIFICIAL INTELLIGENCE FEDERATED LEARNING DATA PRIVACY | ||
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