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Motivated by the imminent growth of massive, highly redundant genomic databases, we study the problem of compressing a string database while simultaneously supporting fast random access, substring extraction and pattern matching to the…

Data Structures and Algorithms · Computer Science 2012-11-01 Travis Gagie , Paweł Gawrychowski , Christopher Hoobin , Simon J. Puglisi

We present the first $\mathrm{o}(n)$-space polynomial-time algorithm for computing the length of a longest common subsequence. Given two strings of length $n$, the algorithm runs in $\mathrm{O}(n^{3})$ time with $\mathrm{O}\left(\frac{n…

Data Structures and Algorithms · Computer Science 2020-09-21 Masashi Kiyomi , Takashi Horiyama , Yota Otachi

We revisit two well-known algorithmic problems on strings: computing a shortest unique substring (SUS) and a shortest absent substring (SAS) of a string $S$ of length $n$. Both problems admit folklore $\mathcal{O}(n)$-time solutions using…

Data Structures and Algorithms · Computer Science 2026-05-07 Panagiotis Charalampopoulos , Manal Mohamed , Solon P. Pissis , Hilde Verbeek , Wiktor Zuba

Many consensus string problems are based on Hamming distance. We replace Hamming distance by the more flexible (e.g., easily coping with different input string lengths) dynamic time warping distance, best known from applications in time…

Discrete Mathematics · Computer Science 2020-02-05 Nathan Schaar , Vincent Froese , Rolf Niedermeier

Strings are a natural representation of biological data such as DNA, RNA and protein sequences. The problem of finding a string that summarizes a set of sequences has direct application in relative compression algorithms for genome and…

Data Structures and Algorithms · Computer Science 2019-12-06 P. Mirabal , J. Abreu , D. Seco

Abelian string matching problems are becoming an object of considerable interest in last years. Very recently, Alatabbi et al. \cite{AILR2015} presented the first solution for the longest common Abelian factor problem for a pair of strings,…

Data Structures and Algorithms · Computer Science 2015-03-12 Szymon Grabowski

We study a fundamental problem in Bayesian learning, where the goal is to select a set of data sources with minimum cost while achieving a certain learning performance based on the data streams provided by the selected data sources. First,…

Machine Learning · Computer Science 2021-05-04 Lintao Ye , Aritra Mitra , Shreyas Sundaram

In this paper, we consider the problem of finding a minimum common partition of two strings. The problem has its application in genome comparison. As it is an NP-hard, discrete combinatorial optimization problem, we employ a metaheuristic…

Artificial Intelligence · Computer Science 2015-06-22 S. M. Ferdous , M. Sohel Rahman

The Set Cover problem (SCP) and Set Packing problem (SPP) are standard NP-hard combinatorial optimization problems. Their decision problem versions are shown to be NP-Complete in Karp's 1972 paper. We specify a rough guide to constructing…

Data Structures and Algorithms · Computer Science 2013-05-16 David Kordalewski

Greedy algorithms have been successfully analyzed and applied in training neural networks for solving variational problems, ensuring guaranteed convergence orders. In this paper, we extend the analysis of the orthogonal greedy algorithm…

Numerical Analysis · Mathematics 2025-04-21 Jinchao Xu , Xiaofeng Xu

We study sketching and streaming algorithms for the Longest Common Subsequence problem (LCS) on strings of small alphabet size $|\Sigma|$. For the problem of deciding whether the LCS of strings $x,y$ has length at least $L$, we obtain a…

Data Structures and Algorithms · Computer Science 2018-10-03 Karl Bringmann , Bhaskar Ray Chaudhury

Finding a minimum vertex cover in a network is a fundamental NP-complete graph problem. One way to deal with its computational hardness, is to trade the qualitative performance of an algorithm (allowing non-optimal outputs) for an improved…

Data Structures and Algorithms · Computer Science 2023-12-14 Thomas Bläsius , Tobias Friedrich , Maximilian Katzmann

A string matching -- and more generally, sequence matching -- algorithm is presented that has a linear worst-case computing time bound, a low worst-case bound on the number of comparisons (2n), and sublinear average-case behavior that is…

Data Structures and Algorithms · Computer Science 2008-10-02 David R. Musser , Gor V. Nishanov

The recently-proposed generic Dijkstra algorithm finds shortest paths in networks with continuous and contiguous resources. While the algorithm was proposed in the context of optical networks (and is applicable to other networks with finite…

Networking and Internet Architecture · Computer Science 2026-03-04 Ireneusz Szcześniak , Bożena Woźna-Szcześniak , Ireneusz Olszewski

Longest common substring (LCS), longest palindrome substring (LPS), and Ulam distance (UL) are three fundamental string problems that can be classically solved in near linear time. In this work, we present sublinear time quantum algorithms…

Quantum Physics · Physics 2023-12-29 François Le Gall , Saeed Seddighin

Given a set of $k$ strings $I$, their longest common subsequence (LCS) is the string with the maximum length that is a subset of all the strings in $I$. A data-structure for this problem preprocesses $I$ into a data-structure such that the…

Data Structures and Algorithms · Computer Science 2021-01-13 Sepideh Aghamolaei

We study sparsity in the max-plus algebraic setting. We seek both exact and approximate solutions of the max-plus linear equation with minimum cardinality of support. In the former case, the sparsest solution problem is shown to be…

Optimization and Control · Mathematics 2019-06-05 Anastasios Tsiamis , Petros Maragos

Two recent lower bounds on the compressibility of repetitive sequences, $\delta \le \gamma$, have received much attention. It has been shown that a length-$n$ string $S$ over an alphabet of size $\sigma$ can be represented within the…

Data Structures and Algorithms · Computer Science 2023-11-10 Tomasz Kociumaka , Gonzalo Navarro , Francisco Olivares

Clustering problems such as $k$-means and $k$-median are staples of unsupervised learning, and many algorithmic techniques have been developed to tackle their numerous aspects. In this paper, we focus on the class of greedy approximation…

Data Structures and Algorithms · Computer Science 2025-10-30 Max Dupré la Tour , David Saulpic

We study the problem of optimal traffic prediction and monitoring in large-scale networks. Our goal is to determine which subset of K links to monitor in order to "best" predict the traffic on the remaining links in the network. We consider…

Data Structures and Algorithms · Computer Science 2013-12-04 Michael Kallitsis , Stilian Stoev , George Michailidis
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