[CFP] MLG 2026: Mining and Learning with Graphs, ECML PKDD 2026

CALL FOR PAPERS

MLG 2026
23rd International Workshop on Mining and Learning with Graphs
Co-located with ECML PKDD 2026
Naples, Italy
Workshop date: 7 or 11 September 2026

Website:
https://mlg-europe.github.io/2026/

Submission deadline:
5 June 2026, 23:59 AoE

The International Workshop on Mining and Learning with Graphs (MLG) 
invites submissions on theoretical, algorithmic, and applied aspects of 
mining and learning with graphs.

Topics of interest include, but are not limited to:

- Theoretical analysis of graph algorithms and graph models
- Computational and statistical learning theory related to graphs
- Graph clustering and community detection
- Pattern mining on graphs
- Graph kernels and metric learning on graphs
- Graph embeddings and representation learning
- Machine learning for combinatorial problems on graphs
- Statistical models of graphs and graph sampling
- Explainable, fair, robust, and privacy-preserving ML on graphs
- Applications involving social, biological, chemical, infrastructure, 
and knowledge graphs
- Benchmarking, reproducibility, libraries, datasets, and tools

We welcome novel research papers, demo papers, dataset papers, 
work-in-progress papers, visionary papers, appraisal papers, relevant 
previously published work, and work that will be presented at the main 
ECML PKDD conference.

Submission guidelines:

Long papers: up to 12 pages
Short papers: up to 8 pages
Format: Springer LNCS style
Review: single-blind

Accepted papers will be published on the workshop website and will not 
be considered archival for resubmission purposes.

Submission site:
https://cmt3.research.microsoft.com/ECMLPKDDWorkshopTrack2026

Please select:
MLG: Mining and Learning with Graphs

Workshop website:
https://mlg-europe.github.io/2026/

-- 
Ass.-Prof. Dr. Yllka Velaj
University of Vienna
Faculty of Computer Science
Währinger Straße 29, A-1090 Vienna
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