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A Note on the Performance of Algorithms for Solving Linear Diophantine Equations in the Naturals ...
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Lexicographically Fair Learning: Algorithms and Generalization ...
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Dynamic Suffix Array with Sub-linear update time and Poly-logarithmic Lookup Time ...
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The Labeled Direct Product Optimally Solves String Problems on Graphs ...
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Breaking the $O(n)$-Barrier in the Construction of Compressed Suffix Arrays ...
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Abstract:
The suffix array, describing the lexicographic order of suffixes of a given text, is the central data structure in string algorithms. The suffix array of a length-$n$ text uses $Θ(n \log n)$ bits, which is prohibitive in many applications. To address this, Grossi and Vitter [STOC 2000] and, independently, Ferragina and Manzini [FOCS 2000] introduced space-efficient versions of the suffix array, known as the compressed suffix array (CSA) and the FM-index. For a length-$n$ text over an alphabet of size $σ$, these data structures use only $O(n \log σ)$ bits. Immediately after their discovery, they almost completely replaced plain suffix arrays in practical applications, and a race started to develop efficient construction procedures. Yet, after more than 20 years, even for $σ=2$, the fastest algorithm remains stuck at $O(n)$ time [Hon et al., FOCS 2003], which is slower by a $Θ(\log n)$ factor than the lower bound of $Ω(n / \log n)$ (following simply from the necessity to read the entire input). We break this ... : 41 pages ...
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Keyword:
Data Structures and Algorithms cs.DS; FOS Computer and information sciences
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URL: https://arxiv.org/abs/2106.12725 https://dx.doi.org/10.48550/arxiv.2106.12725
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FM-Indexing Grammars Induced by Suffix Sorting for Long Patterns ...
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Construction of Sparse Suffix Trees and LCE Indexes in Optimal Time and Space ...
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Detecting Signal Corruptions in Voice Recordings for Speech Therapy ; Igenkänning av Signalproblem i Röstinspelningar för Logopedi
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Nylén, Helmer. - : KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021
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Eliciting Auxiliary Information for Cold Start User Recommendation: A Survey
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In: Applied Sciences ; Volume 11 ; Issue 20 (2021)
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Authorship Attribution of Social Media and Literary Russian-Language Texts Using Machine Learning Methods and Feature Selection
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In: Future Internet; Volume 14; Issue 1; Pages: 4 (2021)
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