Call: IEEE ICMLA 2021

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Sunday, September 5, 2021

Event Details

IEEE International Conference on Machine Learning Applications (ICMLA 2021)
Special Session: Machine Learning for Graphs (ML4Graphs) (submission deadline Sep. 5th 2021)

Graphs or networks are ubiquitous structures that appear in a multitude of complex systems like social networks, biological networks, knowledge graphs, the world wide web, transportation networks, and many more.
This special session at ICMLA 2021 aims to bring researchers across disciplines to share their innovative ideas on learning with graphs and leverage existing methodologies across several application domains. This special session will also serve as a common ground to build collaborations, share datasets, and inspire machine learning on graphs research in areas where there are limitations in the existing approaches. Authors of the best papers from this special session will be invited to extend their work and publish it in selected journals (SNAM, Applied Network Science, and Journal of Intelligent and Information Systems).


Scope:
We welcome novel research papers on the following algorithms and applications, including but not limited to:

Algorithms: Graph representation learning, Hyperbolic graph embedding, Community detection, Node classification, Link prediction, ML on Signed networks, ML on multi-layer and heterogeneous networks, ML on knowledge graphs, ML on dynamic graphs and graph streams, ML on cascades and cascade growth, Network growth models, Graph summarization, Graph partitioning, Network fusion, Scalable ML algorithms for graphs

Applications: Computational social science, Social network analysis, Gender equality, Affective polarization, Echo chambers, Civil unrest, Fake news and misinformation spread, Hate speech and polarization, Population migration, Computer Vision and Natural Language Processing, Question Answering using Knowledge Graphs and Deep Learning, Scene graph generation, Activity understanding from multimodal data, Image and Video captioning, Knowledge graphs for multimodal understanding, Neural-symbolic integration, Explainable methods for visual understanding, senesmaking knowledge graph construction, Applying knowledge graph embeddings to real-world scenarios, Health, Health informatics and analytics, Health misinformation, Disease epidemics, Genomics, Population health, Synthetic population
Submission guidelines and instructions:
Papers submitted for review should conform to IEEE specifications. Manuscript templates can be downloaded from the IEEE website. The maximum length of papers is 8 pages. All the papers will go through a double-blind peer-review process. Authors’ names and affiliations should not appear in the submitted paper. The authors’ prior work should be cited in the third person. Authors should also avoid revealing their identities and/or institutions in the text, figures, links, etc. Papers must be submitted via the CMT System by selecting the track “Special Session on Machine Learning on Graphs”. All accepted papers must be presented by one of the authors, who must register.

Paper Publication: Accepted papers will be published in the IEEE ICMLA 2021 conference proceedings (to be published by IEEE) and indexed via Google Scholar, DBLP, etc.
Important Dates:
 
Submission Deadline: September 5, 2021
Notification of Acceptance: September 26, 2021
Camera-ready papers & Pre-Registration: October 1, 2021
We eagerly anticipate your submissions!