Search results for " Data Structures"

showing 10 items of 80 documents

A Fast Algorithm Finding the Shortest Reset Words

2012

In this paper we present a new fast algorithm finding minimal reset words for finite synchronizing automata. The problem is know to be computationally hard, and our algorithm is exponential. Yet, it is faster than the algorithms used so far and it works well in practice. The main idea is to use a bidirectional BFS and radix (Patricia) tries to store and compare resulted subsets. We give both theoretical and practical arguments showing that the branching factor is reduced efficiently. As a practical test we perform an experimental study of the length of the shortest reset word for random automata with $n$ states and 2 input letters. We follow Skvorsov and Tipikin, who have performed such a s…

FOS: Computer and information sciencesFormal Languages and Automata Theory (cs.FL)Computer Science - Data Structures and AlgorithmsData Structures and Algorithms (cs.DS)Computer Science - Formal Languages and Automata TheoryComputer Science::Formal Languages and Automata Theory
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Fast computation of abelian runs

2016

Given a word $w$ and a Parikh vector $\mathcal{P}$, an abelian run of period $\mathcal{P}$ in $w$ is a maximal occurrence of a substring of $w$ having abelian period $\mathcal{P}$. Our main result is an online algorithm that, given a word $w$ of length $n$ over an alphabet of cardinality $\sigma$ and a Parikh vector $\mathcal{P}$, returns all the abelian runs of period $\mathcal{P}$ in $w$ in time $O(n)$ and space $O(\sigma+p)$, where $p$ is the norm of $\mathcal{P}$, i.e., the sum of its components. We also present an online algorithm that computes all the abelian runs with periods of norm $p$ in $w$ in time $O(np)$, for any given norm $p$. Finally, we give an $O(n^2)$-time offline randomi…

FOS: Computer and information sciencesGeneral Computer ScienceComputationAbelian run[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS]Elementary abelian group0102 computer and information sciences02 engineering and technology01 natural sciencesRank of an abelian groupTheoretical Computer ScienceCombinatoricsComputer Science - Data Structures and Algorithms0202 electrical engineering electronic engineering information engineeringData Structures and Algorithms (cs.DS)[INFO]Computer Science [cs]Online algorithmAbelian groupComputingMilieux_MISCELLANEOUSMathematicsCombinatorics on wordDiscrete mathematicsComputer Science (all)Abelian periodText algorithm16. Peace & justiceSubstringRandomized algorithmCombinatorics on words010201 computation theory & mathematics020201 artificial intelligence & image processingComputer Science::Formal Languages and Automata Theory
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Generating a Gray code for prefix normal words in amortized polylogarithmic time per word

2020

A prefix normal word is a binary word with the property that no substring has more $1$s than the prefix of the same length. By proving that the set of prefix normal words is a bubble language, we can exhaustively list all prefix normal words of length $n$ as a combinatorial Gray code, where successive strings differ by at most two swaps or bit flips. This Gray code can be generated in $\Oh(\log^2 n)$ amortized time per word, while the best generation algorithm hitherto has $\Oh(n)$ running time per word. We also present a membership tester for prefix normal words, as well as a novel characterization of bubble languages.

FOS: Computer and information sciencesGeneral Computer ScienceFormal Languages and Automata Theory (cs.FL)Property (programming)combinatorial Gray codeComputer Science - Formal Languages and Automata TheoryData_CODINGANDINFORMATIONTHEORY0102 computer and information sciences02 engineering and technologyCharacterization (mathematics)01 natural sciencesTheoretical Computer ScienceCombinatoricsSet (abstract data type)Gray codeComputer Science - Data Structures and Algorithms0202 electrical engineering electronic engineering information engineeringData Structures and Algorithms (cs.DS)MathematicsAmortized analysisSettore INF/01 - Informaticaprefix normal wordsSubstringcombinatorial generationPrefixjumbled pattern matching010201 computation theory & mathematics020201 artificial intelligence & image processingbinary languagesprefix normal words binary languages combinatorial Gray code combinatorial generation jumbled pattern matchingWord (computer architecture)Theoretical Computer Science
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ALGORITHMS FOR JUMBLED PATTERN MATCHING IN STRINGS

2011

The Parikh vector p(s) of a string s is defined as the vector of multiplicities of the characters. Parikh vector q occurs in s if s has a substring t with p(t)=q. We present two novel algorithms for searching for a query q in a text s. One solves the decision problem over a binary text in constant time, using a linear size index of the text. The second algorithm, for a general finite alphabet, finds all occurrences of a given Parikh vector q and has sub-linear expected time complexity; we present two variants, which both use a linear size index of the text.

FOS: Computer and information sciencesJ.3average case analysis.Binary numberaverage case analysispermuted stringpermuted stringsComputer Science - Data Structures and AlgorithmsComputer Science (miscellaneous)Parikh vectorData Structures and Algorithms (cs.DS)Pattern matchingTime complexityMathematicsString (computer science)Parikh vectorsstring algorithmDecision problemstring algorithmsSubstringParikh vectors; permuted strings; pattern matching; string algorithms; average case analysisF.2.2; J.3Index (publishing)pattern matchingF.2.2Constant (mathematics)AlgorithmComputer Science::Formal Languages and Automata Theory
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Online shortest paths with confidence intervals for routing in a time varying random network

2018

International audience; The increase in the world's population and rising standards of living is leading to an ever-increasing number of vehicles on the roads, and with it ever-increasing difficulties in traffic management. This traffic management in transport networks can be clearly optimized by using information and communication technologies referred as Intelligent Transport Systems (ITS). This management problem is usually reformulated as finding the shortest path in a time varying random graph. In this article, an online shortest path computation using stochastic gradient descent is proposed. This routing algorithm for ITS traffic management is based on the online Frank-Wolfe approach.…

FOS: Computer and information sciencesMathematical optimizationComputer sciencePopulation02 engineering and technology[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE][INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing[SPI]Engineering Sciences [physics][INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR]0502 economics and business11. SustainabilityComputer Science - Data Structures and Algorithms0202 electrical engineering electronic engineering information engineeringFOS: MathematicsData Structures and Algorithms (cs.DS)educationIntelligent transportation systemMathematics - Optimization and ControlRandom graph050210 logistics & transportationeducation.field_of_studyStochastic process[SPI.PLASMA]Engineering Sciences [physics]/Plasmas05 social sciencesApproximation algorithm[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationStochastic gradient descentOptimization and Control (math.OC)[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]Shortest path problem020201 artificial intelligence & image processing[INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET]Routing (electronic design automation)[INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]
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Variable time amplitude amplification and a faster quantum algorithm for solving systems of linear equations

2010

We present two new quantum algorithms. Our first algorithm is a generalization of amplitude amplification to the case when parts of the quantum algorithm that is being amplified stop at different times. Our second algorithm uses the first algorithm to improve the running time of Harrow et al. algorithm for solving systems of linear equations from O(kappa^2 log N) to O(kappa log^3 kappa log N) where \kappa is the condition number of the system of equations.

FOS: Computer and information sciencesMathematics::LogicQuantum PhysicsComputer Science - Computational ComplexityComputer Science - Data Structures and AlgorithmsFOS: Physical sciencesData Structures and Algorithms (cs.DS)Computational Complexity (cs.CC)Quantum Physics (quant-ph)
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The rightmost equal-cost position problem.

2013

LZ77-based compression schemes compress the input text by replacing factors in the text with an encoded reference to a previous occurrence formed by the couple (length, offset). For a given factor, the smallest is the offset, the smallest is the resulting compression ratio. This is optimally achieved by using the rightmost occurrence of a factor in the previous text. Given a cost function, for instance the minimum number of bits used to represent an integer, we define the Rightmost Equal-Cost Position (REP) problem as the problem of finding one of the occurrences of a factor whose cost is equal to the cost of the rightmost one. We present the Multi-Layer Suffix Tree data structure that, for…

FOS: Computer and information sciencesOffset (computer science)Computer scienceSuffix treeComputer Science - Information Theorylaw.inventionCombinatoricslawLog-log plotComputer Science - Data Structures and AlgorithmsCompression schemetext compressiondictionary text compressionData Structures and Algorithms (cs.DS)LZ77 compressiondata compressionLossless compressionfull text indexSuffix Tree Data StructuresSettore INF/01 - InformaticaInformation Theory (cs.IT)Data structurePrefixCompression ratioCompression scheme; Constant time; Suffix Tree Data StructuresAlgorithmData compressionConstant time
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Whom to befriend to influence people

2020

Alice wants to join a new social network, and influence its members to adopt a new product or idea. Each person $v$ in the network has a certain threshold $t(v)$ for {\em activation}, i.e adoption of the product or idea. If $v$ has at least $t(v)$ activated neighbors, then $v$ will also become activated. If Alice wants to activate the entire social network, whom should she befriend? More generally, we study the problem of finding the minimum number of links that a set of external influencers should form to people in the network, in order to activate the entire social network. This {\em Minimum Links} Problem has applications in viral marketing and the study of epidemics. Its solution can be…

FOS: Computer and information sciencesPhysics - Physics and SocietyGeneral Computer ScienceFOS: Physical sciencesPhysics and Society (physics.soc-ph)0102 computer and information sciences02 engineering and technology01 natural sciencesSocial networksGraphTheoretical Computer ScienceCombinatoricsComputer Science - Data Structures and AlgorithmsGreedy algorithmFOS: Mathematics0202 electrical engineering electronic engineering information engineeringMathematics - CombinatoricsData Structures and Algorithms (cs.DS)Greedy algorithmTime complexityNP-completeMathematicsSocial and Information Networks (cs.SI)Social networkDiscrete mathematicsBinary treeDegree (graph theory)Computer Science (all)Order (ring theory)Computer Science - Social and Information NetworksJoin (topology)Influence maximizationGreedy algorithms010201 computation theory & mathematicsGraphs; Greedy algorithms; Influence maximization; NP-complete; Social networksProduct (mathematics)020201 artificial intelligence & image processingCombinatorics (math.CO)Constant (mathematics)GraphsTheoretical Computer Science
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Quadratic speedup for finding marked vertices by quantum walks

2020

A quantum walk algorithm can detect the presence of a marked vertex on a graph quadratically faster than the corresponding random walk algorithm (Szegedy, FOCS 2004). However, quantum algorithms that actually find a marked element quadratically faster than a classical random walk were only known for the special case when the marked set consists of just a single vertex, or in the case of some specific graphs. We present a new quantum algorithm for finding a marked vertex in any graph, with any set of marked vertices, that is (up to a log factor) quadratically faster than the corresponding classical random walk.

FOS: Computer and information sciencesQuadratic growthQuantum PhysicsQuantum algorithmsSpeedupMarkov chainMarkov chainsProbability (math.PR)FOS: Physical sciencesRandom walkVertex (geometry)CombinatoricsQuadratic equationSearch by random walkQuantum searchComputer Science - Data Structures and AlgorithmsFOS: MathematicsData Structures and Algorithms (cs.DS)Quantum walkQuantum algorithmQuantum Physics (quant-ph)Mathematics - ProbabilityMathematicsQuantum walks
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Search by quantum walks on two-dimensional grid without amplitude amplification

2011

We study search by quantum walk on a finite two dimensional grid. The algorithm of Ambainis, Kempe, Rivosh (quant-ph/0402107) takes O(\sqrt{N log N}) steps and finds a marked location with probability O(1/log N) for grid of size \sqrt{N} * \sqrt{N}. This probability is small, thus amplitude amplification is needed to achieve \Theta(1) success probability. The amplitude amplification adds an additional O(\sqrt{log N}) factor to the number of steps, making it O(\sqrt{N} log N). In this paper, we show that despite a small probability to find a marked location, the probability to be within an O(\sqrt{N}) neighbourhood (at an O(\sqrt[4]{N}) distance) of the marked location is \Theta(1). This all…

FOS: Computer and information sciencesQuantum PhysicsComputer Science - Computational ComplexityComputer Science - Data Structures and AlgorithmsFOS: Physical sciencesData Structures and Algorithms (cs.DS)Computational Complexity (cs.CC)Nuclear ExperimentQuantum Physics (quant-ph)
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