Brief Announcement: Distributed Graph Algorithms with Predictions

We initiate the study of distributed graph algorithms with predictions in synchronous message passing systems. Each node in the graph is given a prediction, which is some extra information about the problem instance that may be incorrect. The better the prediction, the fewer rounds the algorithm should perform. We present a framework for evaluating distributed graph algorithms with predictions and some methods for transforming existing algorithms without predictions to effectively use predictions. Our approach is illustrated using the Maximal Independent Set problem.

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Publication Details

Published
2025-06-13
DOI
https://doi.org/10.1145/3732772.3733530
Citations
1
Primary Topic
Complexity and Algorithms in Graphs
Type
article
Field-Weighted Citation Impact
1.50

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article

Brief Announcement: Distributed Graph Algorithms with Predictions

Kim S. Larsen, Faith Ellen, Joan Boyar
1 citations
Complexity and Algorithms in Graphs
1.50
article

Brief Announcement: Distributed Graph Algorithms with Predictions

Kim S. Larsen, Faith Ellen, Joan Boyar
article en
1 citations

Abstract

We initiate the study of distributed graph algorithms with predictions in synchronous message passing systems. Each node in the graph is given a prediction, which is some extra information about the problem instance that may be incorrect. The better the prediction, the fewer rounds the algorithm should perform. We present a framework for evaluating distributed graph algorithms with predictions and some methods for transforming existing algorithms without predictions to effectively use predictions. Our approach is illustrated using the Maximal Independent Set problem.

University of Southern Denmark (DK), University of Toronto (CA)
Natural Sciences and Engineering Research Council of Canada
Openalex Percentile: Top 16%
Complexity and Algorithms in Graphs
1.50
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