Search results for "Time complexity"

showing 10 items of 99 documents

Adaptive learning of compressible strings

2020

Suppose an oracle knows a string $S$ that is unknown to us and that we want to determine. The oracle can answer queries of the form "Is $s$ a substring of $S$?". In 1995, Skiena and Sundaram showed that, in the worst case, any algorithm needs to ask the oracle $\sigma n/4 -O(n)$ queries in order to be able to reconstruct the hidden string, where $\sigma$ is the size of the alphabet of $S$ and $n$ its length, and gave an algorithm that spends $(\sigma-1)n+O(\sigma \sqrt{n})$ queries to reconstruct $S$. The main contribution of our paper is to improve the above upper-bound in the context where the string is compressible. We first present a universal algorithm that, given a (computable) compre…

FOS: Computer and information sciencesCentroid decompositionGeneral Computer ScienceString compressionAdaptive learningKolmogorov complexityContext (language use)Data_CODINGANDINFORMATIONTHEORYString reconstructionTheoretical Computer ScienceCombinatoricsString reconstruction; String learning; Adaptive learning; Kolmogorov complexity; String compression; Lempel-Ziv; Centroid decomposition; Suffix treeSuffix treeIntegerComputer Science - Data Structures and AlgorithmsOrder (group theory)Data Structures and Algorithms (cs.DS)Adaptive learning; Centroid decomposition; Kolmogorov complexity; Lempel-Ziv; String compression; String learning; String reconstruction; Suffix treeTime complexityComputer Science::DatabasesMathematicsLempel-ZivSettore INF/01 - InformaticaLinear spaceString (computer science)SubstringBounded functionString learningTheoretical Computer Science
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A subquadratic algorithm for minimum palindromic factorization

2014

We give an $\mathcal{O}(n \log n)$-time, $\mathcal{O}(n)$-space algorithm for factoring a string into the minimum number of palindromic substrings. That is, given a string $S [1..n]$, in $\mathcal{O}(n \log n)$ time our algorithm returns the minimum number of palindromes $S_1,\ldots, S_\ell$ such that $S = S_1 \cdots S_\ell$. We also show that the time complexity is $\mathcal{O}(n)$ on average and $\Omega(n\log n)$ in the worst case. The last result is based on a characterization of the palindromic structure of Zimin words.

FOS: Computer and information sciencesDiscrete Mathematics (cs.DM)PalindromeCharacterization (mathematics)Binary logarithmOmegaSubstringTheoretical Computer ScienceString algorithmComputational Theory and MathematicsFactorizationComputer Science - Data Structures and AlgorithmsC++ string handlingPalindromeDiscrete Mathematics and CombinatoricsData Structures and Algorithms (cs.DS)FactorizationTime complexityAlgorithmMathematicsComputer Science - Discrete Mathematics
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Finite state verifiers with constant randomness

2014

We give a new characterization of $\mathsf{NL}$ as the class of languages whose members have certificates that can be verified with small error in polynomial time by finite state machines that use a constant number of random bits, as opposed to its conventional description in terms of deterministic logarithmic-space verifiers. It turns out that allowing two-way interaction with the prover does not change the class of verifiable languages, and that no polynomially bounded amount of randomness is useful for constant-memory computers when used as language recognizers, or public-coin verifiers. A corollary of our main result is that the class of outcome problems corresponding to O(log n)-space …

FOS: Computer and information sciencesDiscrete mathematicsClass (set theory)Computer Science - Logic in Computer ScienceFinite-state machineGeneral Computer ScienceComputational Complexity (cs.CC)Binary logarithmLogic in Computer Science (cs.LO)Theoretical Computer ScienceComputer Science - Computational ComplexityBounded functionVerifiable secret sharingConstant (mathematics)Time complexityRandomnessMathematics
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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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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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Exact affine counter automata

2017

We introduce an affine generalization of counter automata, and analyze their ability as well as affine finite automata. Our contributions are as follows. We show that there is a language that can be recognized by exact realtime affine counter automata but by neither 1-way deterministic pushdown automata nor realtime deterministic k-counter automata. We also show that a certain promise problem, which is conjectured not to be solved by two-way quantum finite automata in polynomial time, can be solved by Las Vegas affine finite automata. Lastly, we show that how a counter helps for affine finite automata by showing that the language MANYTWINS, which is conjectured not to be recognized by affin…

FOS: Computer and information sciencesTheoryofComputation_COMPUTATIONBYABSTRACTDEVICESautomataFormal Languages and Automata Theory (cs.FL)GeneralizationComputer scienceFOS: Physical sciencesComputer Science - Formal Languages and Automata Theorycounter automataМатематика0102 computer and information sciences02 engineering and technologyComputational Complexity (cs.CC)01 natural sciencesquantum computinglcsh:QA75.5-76.95Deterministic pushdown automatonComputer Science (miscellaneous)0202 electrical engineering electronic engineering information engineeringQuantum finite automataPromise problemTime complexityDiscrete mathematicsQuantum Physicscomputational complexityFinite-state machinelcsh:MathematicsИнформатикаpushdown automatalcsh:QA1-939Nonlinear Sciences::Cellular Automata and Lattice GasesКибернетикаAutomatonComputer Science - Computational ComplexityTheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGES010201 computation theory & mathematics020201 artificial intelligence & image processinglcsh:Electronic computers. Computer scienceAffine transformationaffine computingQuantum Physics (quant-ph)Computer Science::Formal Languages and Automata Theory
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Parallel Algorithms for Listing Well-Formed Parentheses Strings

1998

We present two cost-optimal parallel algorithms generating the set of all well-formed parentheses strings of length 2n with constant delay for each generated string. In our first algorithm we generate in lexicographic order well-formed parentheses strings represented by bitstrings, and in the second one we use the representation by weight sequences. In both cases the computational model is based on an architecture CREW PRAM, where each processor performs the same algorithm simultaneously on a different set of data. Different processors can access the shared memory at the same time to read different data in the same or different memory locations, but no two processors are allowed to write i…

Gray codeSet (abstract data type)Shared memoryHardware and ArchitectureComputer scienceString (computer science)Parallel algorithmParallel random-access machineLexicographical orderTime complexityAlgorithmSoftwareTheoretical Computer ScienceParallel Processing Letters
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Solving NP-Complete Problems with Networks of Evolutionary Processors

2001

We propose a computational device based on evolutionary rules and communication within a network, similar to that introduced in [4], called network of evolutionary processors. An NP-complete problem is solved by networks of evolutionary processors of linear size in linear time. Some furher directions of research are finally discussed.

Knowledge basebusiness.industryComputer scienceEvolutionary algorithmQuantitative Biology::Populations and EvolutionArtificial intelligencebusinesscomputer.software_genreNP-completeTime complexitycomputerEvolutionary programmingExpert system
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Robust control of a Hammerstein model of DC/DC converters

2007

This paper deals with the robust control of a Hammerstein mathematical model of DC/DC converters, consisting of the nonlinear static characteristics of the converter followed by one of a few number of linear time- invariant models which describe the converter in the useful working range. One of these models is assumed as the nominal model of the system and the remaining models are used for describing the model uncertainty. Nominal behaviour is assured using H-2 optimal control method, Robust stability and behaviour are assured by imposing H-infin specifications. The closed loop control system consisting of the converter Hammerstein model and the robust controller is analyzed by means of sim…

Linear systemControl engineeringInvariant (physics)ConvertersOptimal controlRobust controllersWorking rangeNonlinear systemSettore ING-INF/04 - AutomaticaControl theoryNonlinear static characteristicRobust controlHammerstein modelTime complexityMathematics2007 46th IEEE Conference on Decision and Control
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From First Principles to the Burrows and Wheeler Transform and Beyond, via Combinatorial Optimization

2007

AbstractWe introduce a combinatorial optimization framework that naturally induces a class of optimal word permutations with respect to a suitably defined cost function taking into account various measures of relatedness between words. The Burrows and Wheeler transform (bwt) (cf. [M. Burrows, D. Wheeler, A block sorting lossless data compression algorithm, Technical Report 124, Digital Equipment Corporation, 1994]), and its analog for labelled trees (cf. [P. Ferragina, F. Luccio, G. Manzini, S. Muthukrishnan, Structuring labeled trees for optimal succinctness, and beyond, in: Proc. of the 45th Annual IEEE Symposium on Foundations of Computer Science, 2005, pp. 198–207]), are special cases i…

Lossless compressionBoosting (machine learning)General Computer ScienceComputer scienceComputationData_CODINGANDINFORMATIONTHEORYLyndon wordOptimal word permutationTheoretical Computer ScienceCombinatoricsPermutationSuffix treeCombinatorial optimizationBurrows–Wheeler transformTime complexityComputer Science(all)
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