aappr.jl
Accelerated and Sparse Algorithms for Approximate Personalized PageRank and Beyond
Science Score: 28.0%
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✓CITATION.cff file
Found CITATION.cff file -
○codemeta.json file
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Low similarity (7.5%) to scientific vocabulary
Repository
Accelerated and Sparse Algorithms for Approximate Personalized PageRank and Beyond
Basic Info
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Metadata Files
README.md
aappr
Code for the paper Martínez-Rubio, D., Wirth, E. and Pokutta, S., 2023. Accelerated and sparse algorithms for approximate personalized pagerank and beyond. arXiv preprint arXiv:2303.12875.
COLT 2023 version: [Martínez-Rubio, D., Wirth, E. and Pokutta, S., 2023. Accelerated and sparse algorithms for approximate personalized pagerank and beyond. In Proceedings of the 36th Conference on Learning Theory, pages 2852–2876. PMLR, 2023.]
How to use this repository
Tests: After downloading and setting up the environment, one should run test/run_tests.jl to make sure that everything is working correctly.
Workflow: The file example.jl contains a detailed overview of how the different algorithms, ASPR, CASPR, CDPR, FISTA, and ISTA can all be used for local graph clustering.
Experiments: The experiment parameters are stored in the file experiments/experimentparameters.jl. To perform the experiments from the paper, run experiments/performruns.jl, which will store the results in results.jls. To visualize the experiments from the paper, run experiments/visualizeresults.jl. The plots will be stored in the figures folder. Finally, to get stats on the datasets used, run experiments/datasetsstats.jl.
Owner
- Name: IOL Lab
- Login: ZIB-IOL
- Kind: organization
- Location: Germany
- Website: https://iol.zib.de
- Repositories: 27
- Profile: https://github.com/ZIB-IOL
Working on optimization and learning at the intersection of mathematics and computer science
Citation (CITATION.bib)
@article{martinez2023accelerated,
title={Accelerated and Sparse Algorithms for Approximate Personalized PageRank and Beyond},
author={Mart{\'\i}nez-Rubio, David and Wirth, Elias and Pokutta, Sebastian},
journal={arXiv preprint arXiv:2303.12875},
year={2023}
}
@InProceedings{martinezrubio2023accelerated,
author={Mart{\'\i}nez-Rubio, David and Wirth, Elias and Pokutta, Sebastian},
title={Accelerated and Sparse Algorithms for Approximate Personalized PageRank and Beyond},
booktitle = {Proceedings of the 36th Conference on Learning Theory},
year = {2023},
pages = {2852--2876},
volume = {195},
organization={PMLR}
}
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