The 5th International Workshop on Machine Learning on Graphs (MLoG)
Pages 1210 - 1211
Abstract
Graphs, which encode pairwise relations between entities, are a kind of universal data structure for a lot of real-world data, including social networks, transportation networks, and chemical molecules. Many important applications on these data can be treated as computational tasks on graphs. Recently, machine learning techniques are widely developed and utilized to effectively tame graphs for discovering actionable patterns and harnessing them for advancing various graph-related computational tasks. Huge success has been achieved and numerous real-world applications have benefited from it. However, since in today's world, we are generating and gathering data in a much faster and more diverse way, real-world graphs are becoming increasingly large-scale and complex. More dedicated efforts are needed to propose more advanced machine learning techniques and properly deploy them for real-world applications in a scalable way. Thus, we organize The 5th International Workshop on Machine Learning on Graphs (MLoG) (https://mlog-workshop.github.io/wsdm24.html), held in conjunction with the 17th ACM Conference on Web Search and Data Mining (WSDM), which provides a venue to gather academia researchers and industry researchers/practitioners to present the recent progress on machine learning on graphs.
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- The 5th International Workshop on Machine Learning on Graphs (MLoG)
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The 3rd International Workshop on Machine Learning on Graphs (MLoG)
WSDM '23: Proceedings of the Sixteenth ACM International Conference on Web Search and Data MiningGraphs, which encode pairwise relations between entities, are a kind of universal data structure for a lot of real-world data, including social networks, transportation networks, and chemical molecules. Many important applications on these data can be ...
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Information
Published In
March 2024
1246 pages
ISBN:9798400703713
DOI:10.1145/3616855
- General Chairs:
- Luz Angélica,
- Silvio Lattanzi,
- Andrés Muñoz Medina,
- Program Chairs:
- Leman Akoglu,
- Aristides Gionis,
- Sergei Vassilvitskii
Copyright © 2024 Owner/Author.
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 04 March 2024
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Conference
WSDM '24: The 17th ACM International Conference on Web Search and Data Mining
March 4 - 8, 2024
Merida, Mexico
Acceptance Rates
Overall Acceptance Rate 498 of 2,863 submissions, 17%
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