6th International Workshop on Distributed Machine Learning for the Intelligent Computing Continuum (DML-ICC)
In conjunction with the 19th IEEE/ACM International Conference on Utility and Cloud Computing (UCC 2026)
01-04 December, 2026
Florianópolis, Brazil

http://www.lrc.ic.unicamp.br/dml-icc/

### Background ###
As the cloud extends to the fog and to the edge, computing services can be scattered over a set of computing resources that encompass users' devices, the cloud, and intermediate computing infrastructure deployed in between. Moreover, increasing networking capacity promises lower delays in data transfers, enabling a continuum of computing capacity that can be used to process large amounts of data with reduced response times. Such large amounts of data are frequently processed through machine learning approaches, seeking to extract knowledge from raw data generated and consumed by a widely heterogeneous set of applications. Distributed machine learning has been evolving as a tool to run learning tasks also at the edge, often immediately after the data is produced, instead of transferring data to the centralized cloud for later aggregation and processing.

Following the successful editions of DML-ICC between 2022 and 2025, this fifth edition of DML-ICC keeps the aim to be a forum for discussion among researchers with a distributed machine learning background and researchers from parallel/distributed systems and computer networks. By bringing together these research topics, we look forward in building an Intelligent Computing Continuum, where distributed machine learning models can seamlessly run on any device from the edge to the cloud, creating a distributed computing system that is able to fulfill highly heterogeneous applications requirements and build knowledge from data generated by these applications.


### Topics ###
DML-ICC 2026 workshop aims to attract researchers from the machine learning community, especially the ones involved with distributed machine learning techniques, and researchers from the parallel/distributed computing communities. Together, these researchers will be able to build resource management mechanisms that are able to fulfill machine learning jobs requirements, but also use machine learning techniques to improve resource management in large distributed systems. Topics of interest include but are not limited to:

- Agentic edge and AI agents in the continuum
- Autonomic Computing in the Continuum
- Business and Cost Models for the Computing Continuum
- Complex Event Processing and Stream Processing
- Computing and Networking Slicing for the Continuum
- Distributed Machine Learning for Resource Management and Scheduling
- Distributed Machine Learning in the Computing Continuum
- Distributed Machine Learning applications
- Distributed Machine Learning performance evaluation
- Federated Learning
- Intelligent Computing Continuum architectures and models
- Management of Distributed Learning tasks
- Mobility support in the Computing Continuum
- Network management in the Computing Continuum
- Privacy using Distributed Learning
- Programming models for the Computing Continuum
- Resource management and Scheduling in the computing continuum
- Smart Environments (Smart Cities, Smart Buildings, Smart Industry, etc.)
- Theoretical Modeling for the Computing Continuum

### Submissions ###

Paper submission through EasyChair:
https://easychair.org/conferences/?conf=dmlicc2026

The DML-ICC workshop invites authors to submit original and unpublished work. Papers should not exceed 6 pages in IEEE double-column format, including figures, tables, and references. Up to 2 additional pages might be purchased upon the approval of the proceedings chair.

All manuscripts will undergo a double-blind review process and will be reviewed and judged on correctness, originality, technical strength, rigour in analysis, quality of results, quality of presentation, and interest and relevance to the conference attendees. The submitted document should not include author information and should not include acknowledgements, citations or discussion of related work that would make the authorship apparent. Submissions containing author identifying information may be subject to rejection without review.

Submission requires the willingness of at least one of the authors to register as author, non-student rate and present the paper in person.

At least one author of each paper must be registered for the conference for the paper to be published in the proceedings. The conference proceedings will be published by IEEE and made available online via the IEEE Xplore Digital Library.

Please check the DML-ICC webpage for more details on paper format: http://www.lrc.ic.unicamp.br/dml-icc/

### Important Dates ###
Important Dates
Paper submission (Extended): September 15, 2026
Notification to Authors: October 05, 2026
Camera ready submission: October 15, 2026
Workshop date: 01-04 December 2026


### DML-ICC Honorary Chairs ###
- Ian Foster, University of Chicago and Argonne National Laboratory, USA
- Filip De Turck, Ghent University, Belgium

### DML-ICC Co-Chairs ###
Allan M. de Souza, Universidade Estadual de Campinas, Brazil
Karima Velasquez, University of Coimbra, Portugal
Luiz F. Bittencourt, Universidade Estadual de Campinas, Brazil

### Program Committee (TBC) ###
- Atakan Aral, University of Vienna, Austria
- Valeria Cardellini, University of Rome Tor Vergata, Italy
- Bruno Casella, University of Turin, Italy
- Alexandru Costan, INRIA, France
- Fodil Fadli, Qatar University, Qatar
- Reza Farahani, University of Klagenfurt, Austria
- Antonio Filograna, Engineering Ingegneria Informatica, Italy
- Mohammadreza Hoseinyfarahabady, University of Sydney, Australia
- Stefano Iannucci, University of Rome III, Italy
- Shashikant Ilager, University of Amsterdam, Netherlands
- Mohammad Reza Jabbarpour, Swinburne University of Technology, Australia
- Devki Nandan Jha, Newcastle University, UK
- Carlos Kamienski, Federal University of ABC, Brazil
- Wei Li, University of Sydney, Australia
- Zoltán Mann, University of Amsterdam, Netherlands
- Gianluca Mittone, Univeristy of Turin, Italia
- Radu Prodan, University of Innsbruck, Austria
- Rizos Sakellariou, University of Manchester, UK
- Tomasz Szydlo, Newcastle University, UK
- Javid Taheri, Karlstad University, Sweden
- Eirini Eleni Tsiropoulou, Arizona State University, USA