[CFP] ECML-PKDD 2025 - 3rd Workshop on Advancements in Federated Learning (WAFL)

[Mirko Polato]

!! Deadline Extended !!
CALL FOR PAPERS - ECML-PKDD 2025 Workshop
3rd Workshop on Advancements in Federated Learning (WAFL)

DEADLINES
Paper submission: June 22, 2025 (23:59 AoE)
Notification of acceptance: July 14, 2025
Final paper submission: TBA
Conference: September 15 - 19, 2025

WEBSITE
https://wafl2025.di.unito.it/

DESCRIPTION
AI-based systems, especially those based on machine learning technologies, have become central in modern societies. In the meanwhile, users and legislators are becoming aware of privacy issues. Users are increasingly reluctant to share their sensitive information, and new laws have been enacted to regulate how private data is handled (e.g., the GDPR).

Federated Learning (FL) has been proposed to develop better AI systems without compromising users’ privacy and the legitimate interests of private companies. Although still in its infancy, FL has already shown significant theoretical and practical results making FL one of the hottest topics in the machine learning community.

Given the considerable potential in overcoming the challenges of protecting users’ privacy while making the most of available data, we propose WAFL (Workshop on Advancements in Federated Learning Technologies) at ECML-PKDD 2025.

This workshop aims to focus the attention of the ECML-PKDD research community on addressing the open questions and challenges in this thriving research area. Given the broad range of competencies in the ECML-PKDD community, the workshop will welcome foundational contributions and contributions expanding the scope of these techniques, such as improvements in the interpretability and fairness of the learned models.

TOPICS AND THEMES
The WAFL workshop will be centered on the theme of improving and studying the Federated Learning setting. It will welcome applicative and theoretical contributions as well as contributions about specific settings and benchmarking tools. The topics include (but are not limited to):

- Algorithmic and theoretical advances in FL
- Federated Learning with non-iid data distributions
- Security and privacy of FL systems (e.g., differential privacy, adversarial attacks, poisoning attacks, inference attacks, data anonymization, model distillation, secure multi-party computation ...)
- Other non-functional properties of FL (e.g., fairness, interpretability/explainability, personalization ...)
- FL variants and Decentralized Federated Learning (e.g., vertical FL, split-learning, gossip learning, ...)
- Applications of FL (e.g., FL for healthcare, FL on edge devices, advertising, social network, blockchain, web search ...)
- Tools and resources (e.g., benchmark datasets, software libraries, ...)


SUBMISSION
We accept the following types of submissions:

- Short Papers (6 pages + references): Work-in-progress, position papers, or open problems. Accepted short papers will be included in the Springer Workshop Proceedings of ECML-PKDD 2025. Short papers must follow the ECML-PKDD 2025 formatting guidelines (see here).

- Long Papers (12 pages + references): Novel, original research not published elsewhere. Accepted long papers will be included in the Springer Workshop Proceedings of ECML-PKDD 2025. Long papers must follow the ECML-PKDD 2025 formatting guidelines (see here).

- Non-archival Submissions: Papers recently accepted or under review at other venues. These submissions have no formatting restrictions but must be accompanied by a cover letter explaining their relevance to the workshop. Non-archival submissions will not be included in the Springer Workshop Proceedings and will undergo a different selection process by the workshop organizers.

For more details, please visit the workshop's website.

ORGANIZERS
Dr. Mirko Polato, Department of Computer Science, University of Turin, Italy
Prof. Roberto Esposito, Department of Computer Science, University of Turin, Italy