The 1st Workshop on Federated Learning for Unbounded and Intelligent Decentralization (FLUID)
The FLUID Workshop is a premier event aimed at fostering collaboration and knowledge exchange among experts, researchers, and professionals working on Federated Learning (FL) and decentralized systems. FL is an emerging paradigm that enables multiple devices or nodes to collaboratively train machine learning models without exchanging raw data, ensuring data privacy and reducing communication overhead. This technology is becoming increasingly critical in today’s data-driven world.
Why is Federated Learning important? As data grows exponentially across industries like healthcare, finance, smart cities, and the Internet of Things (IoT), traditional centralized machine learning approaches face challenges in terms of privacy, data ownership, and scalability. Federated Learning offers a solution by allowing data to remain localized while still enabling global model improvements. This makes FL essential for scenarios where data privacy, security, and real-time processing are paramount.
The FLUID Workshop will explore key topics, including:
- New algorithms for Federated Learning with unbounded and heterogeneous data
- Privacy-preserving methods in FL
- FL applications in critical areas such as healthcare, smart cities, and IoT
- Security, robustness, and trust in decentralized systems
- Handling non-IID data and heterogeneity in FL
- Decentralized intelligence in multi-agent and IoT environments
This workshop will serve as a platform for researchers to present novel ideas, showcase their latest developments, and engage in discussions that will shape the future of Federated Learning and decentralized AI systems. Don’t miss the opportunity to be part of this groundbreaking event!
Visit the FLUID Workshop Website