Ganesh, Arun, Kociumaka, Tomasz, Loncoln, Andrea, and and Saha, Barna. How Compression and Approximation Affect Efficiency in String Distance Measures. Retrieved from https://par.nsf.gov/biblio/10314274. Proceedings of the 2022 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA) . Web. doi:10.1137/1.9781611977073.112.
Ganesh, Arun, Kociumaka, Tomasz, Loncoln, Andrea, & and Saha, Barna. How Compression and Approximation Affect Efficiency in String Distance Measures. Proceedings of the 2022 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), (). Retrieved from https://par.nsf.gov/biblio/10314274. https://doi.org/10.1137/1.9781611977073.112
Ganesh, Arun, Kociumaka, Tomasz, Loncoln, Andrea, and and Saha, Barna.
"How Compression and Approximation Affect Efficiency in String Distance Measures". Proceedings of the 2022 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA) (). Country unknown/Code not available. https://doi.org/10.1137/1.9781611977073.112.https://par.nsf.gov/biblio/10314274.
@article{osti_10314274,
place = {Country unknown/Code not available},
title = {How Compression and Approximation Affect Efficiency in String Distance Measures},
url = {https://par.nsf.gov/biblio/10314274},
DOI = {10.1137/1.9781611977073.112},
abstractNote = {},
journal = {Proceedings of the 2022 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA)},
author = {Ganesh, Arun and Kociumaka, Tomasz and Loncoln, Andrea and and Saha, Barna},
}
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