Search results for "algorithm"

showing 10 items of 4887 documents

Hierarchies of probabilistic and team FIN-learning

2001

AbstractA FIN-learning machine M receives successive values of the function f it is learning and at some moment outputs a conjecture which should be a correct index of f. FIN learning has two extensions: (1) If M flips fair coins and learns a function with certain probability p, we have FIN〈p〉-learning. (2) When n machines simultaneously try to learn the same function f and at least k of these machines output correct indices of f, we have learning by a [k,n]FIN team. Sometimes a team or a probabilistic learner can simulate another one, if their probabilities p1,p2 (or team success ratios k1/n1,k2/n2) are close enough (Daley et al., in: Valiant, Waranth (Eds.), Proc. 5th Annual Workshop on C…

Discrete mathematics020203 distributed computingProbabilistic learningConjectureFinGeneral Computer ScienceIndex (typography)Probabilistic logicInductive inference0102 computer and information sciences02 engineering and technologyFunction (mathematics)01 natural sciencesTheoretical Computer ScienceMoment (mathematics)Computational learning theory010201 computation theory & mathematics0202 electrical engineering electronic engineering information engineeringTeam learningAlgorithmComputer Science(all)MathematicsTheoretical Computer Science
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Adjacent vertices can be hard to find by quantum walks

2018

Quantum walks have been useful for designing quantum algorithms that outperform their classical versions for a variety of search problems. Most of the papers, however, consider a search space containing a single marked element. We show that if the search space contains more than one marked element, their placement may drastically affect the performance of the search. More specifically, we study search by quantum walks on general graphs and show a wide class of configurations of marked vertices, for which search by quantum walk needs Ω(N) steps, that is, it has no speed-up over the classical exhaustive search. The demonstrated configurations occur for certain placements of two or more adjace…

Discrete mathematics0209 industrial biotechnologyControl and OptimizationComputer science010102 general mathematicsBrute-force search02 engineering and technologyGrid01 natural sciencesGraphHuman-Computer InteractionComputational Mathematics020901 industrial engineering & automationBipartite graphQuantum algorithmQuantum walkHypercube0101 mathematicsVariety (universal algebra)Element (category theory)Block (data storage)Discrete Models in Control Systems Theory
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Longest Motifs with a Functionally Equivalent Central Block

2004

International audience; This paper presents a generalization of the notion of longest repeats with a block of k don't care symbols introduced by [Crochemore et al., LATIN 2004] (for k fixed) to longest motifs composed of three parts: a first and last that parameterize match (that is, match via some symbol renaming, initially unknown), and a functionally equivalent central block. Such three-part motifs are called longest block motifs. Different types of functional equivalence, and thus of matching criteria for the central block are considered, which include as a subcase the one treated in [Crochemore et al., LATIN 2004] and extend to the case of regular expressions with no Kleene closure or …

Discrete mathematics0303 health sciences[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS]Block (permutation group theory)0102 computer and information sciences01 natural sciencesCombinatoricsKleene algebra03 medical and health sciencesClosure (mathematics)010201 computation theory & mathematicsAlgorithmicsKleene starRegular expressionTime complexity030304 developmental biologyMathematicsComplement (set theory)
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An Efficient Algorithm for the Generation of Z-Convex Polyominoes

2014

We present a characterization of Z-convex polyominoes in terms of pairs of suitable integer vectors. This lets us design an algorithm which generates all Z-convex polyominoes of size n in constant amortized time.

Discrete mathematicsAmortized analysisMathematics::CombinatoricsSettore INF/01 - InformaticaPolyominoEfficient algorithmRegular polygonComputer Science::Computational GeometryCharacterization (mathematics)CombinatoricsIntegerComputer Science::Discrete MathematicsTheoryofComputation_ANALYSISOFALGORITHMSANDPROBLEMCOMPLEXITYConstant (mathematics)TetrominoZ-convex polyominoes generation.Mathematics
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Grundy coloring for power graphs

2003

International audience

Discrete mathematicsApplied Mathematics[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS][ INFO.INFO-DM ] Computer Science [cs]/Discrete Mathematics [cs.DM][INFO.INFO-DS] Computer Science [cs]/Data Structures and Algorithms [cs.DS][INFO.INFO-DM]Computer Science [cs]/Discrete Mathematics [cs.DM]Power (physics)Brooks' theoremGreedy coloring[INFO.INFO-DM] Computer Science [cs]/Discrete Mathematics [cs.DM]Discrete Mathematics and Combinatorics[ INFO.INFO-DS ] Computer Science [cs]/Data Structures and Algorithms [cs.DS]ComputingMilieux_MISCELLANEOUSMathematics
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Partially Square Graphs, Hamiltonicity and Circumference II

2000

Abstract Given a graph G, its partially square graph G∗ is a graph obtained by adding an edge uv for each pair u, v of vertices of G at distance 2 whenever the vertices u and v have a common neighbor x satisfying the condition NG(x) ⊆ NG[u] ∪ NG[v], where NG[x]= NG(x) ∪ {x}. In case G is a claw-free graph, G∗ is equal to G2, We define σ ∗ t = min{ ∑ x∈ d ∗ G (x): S is an independent set in G ∗ and ∣S∣ = t} , where d ∗ G (x) = ∣{y ∈ V∣ xy ∈ E(G∗)}∣ . We give for hamiltonicity and circumference new sufficient conditions depending on and we improve some known results.

Discrete mathematicsApplied Mathematics[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS][INFO.INFO-DS] Computer Science [cs]/Data Structures and Algorithms [cs.DS][INFO.INFO-DM]Computer Science [cs]/Discrete Mathematics [cs.DM]CircumferenceDistance-regular graphGraphCombinatorics[INFO.INFO-DM] Computer Science [cs]/Discrete Mathematics [cs.DM]Graph powerIndependent setCommon neighborDiscrete Mathematics and CombinatoricsBound graphComputingMilieux_MISCELLANEOUSMathematics
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Forbidden words in symbolic dynamics

2000

AbstractWe introduce an equivalence relation≃between functions from N to N. By describing a symbolic dynamical system in terms of forbidden words, we prove that the≃-equivalence class of the function that counts the minimal forbidden words of a system is a topological invariant of the system. We show that the new invariant is independent from previous ones, but it is not characteristic. In the case of sofic systems, we prove that the≃-equivalence of the corresponding functions is a decidable question. As a more special application, we show, by using the new invariant, that two systems associated to Sturmian words having “different slope” are not conjugate.

Discrete mathematicsApplied Mathematicsautomata and formal languages010102 general mathematics[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS]Symbolic dynamics[INFO.INFO-DS] Computer Science [cs]/Data Structures and Algorithms [cs.DS]0102 computer and information sciencesFunction (mathematics)16. Peace & justice01 natural sciencesDecidabilitysymbolic dynamics010201 computation theory & mathematicsEquivalence relationcombinatoric on words0101 mathematicsInvariant (mathematics)Dynamical system (definition)Equivalence (measure theory)Computer Science::Formal Languages and Automata TheoryWord (group theory)ComputingMilieux_MISCELLANEOUSMathematics
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Exact, efficient, and complete arrangement computation for cubic curves

2006

AbstractThe Bentley–Ottmann sweep-line method can compute the arrangement of planar curves, provided a number of geometric primitives operating on the curves are available. We discuss the reduction of the primitives to the analysis of curves and curve pairs, and describe efficient realizations of these analyses for planar algebraic curves of degree three or less. We obtain a complete, exact, and efficient algorithm for computing arrangements of cubic curves. Special cases of cubic curves are conics as well as implicitized cubic splines and Bézier curves.The algorithm is complete in that it handles all possible degeneracies such as tangential intersections and singularities. It is exact in t…

Discrete mathematicsArrangementsControl and OptimizationComputationAlgebraic curvesMathematical analysisBézier curveSweep line algorithmComputer Science ApplicationsModuli of algebraic curvesComputational MathematicsGeometric designComputational Theory and MathematicsFamily of curvesSweep-line algorithmExact geometric computationGeometric primitiveAlgebraic curveGeometry and TopologyRobustnessComputingMethodologies_COMPUTERGRAPHICSMathematicsComputational Geometry
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Analysis of Optimal High Resolution and Fixed Rate Scalar Quantization

2009

In 2001, Hui and Neuhoff proposed a uniform quantizer with overload for the quantization of scalar signals and derived the asymptotically optimal size of the quantization bins in the high-bitrate limit. The purpose of the present paper is to prove a quantitatively more precise version of this result which, at the same time, is valid for a more general, quite natural class of probability distributions that requires only little regularity and includes, for instance, positive Lipschitz-continuous functions of unit integral.

Discrete mathematicsAsymptotically optimal algorithmScalar quantizationQuantization (signal processing)Applied mathematicsHigh resolutionProbability distributionLibrary and Information SciencesInformation theoryNatural classComputer Science ApplicationsInformation SystemsMathematicsIEEE Transactions on Information Theory
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Algorithmic Information Theory and Computational Complexity

2013

We present examples where theorems on complexity of computation are proved using methods in algorithmic information theory. The first example is a non-effective construction of a language for which the size of any deterministic finite automaton exceeds the size of a probabilistic finite automaton with a bounded error exponentially. The second example refers to frequency computation. Frequency computation was introduced by Rose and McNaughton in early sixties and developed by Trakhtenbrot, Kinber, Degtev, Wechsung, Hinrichs and others. A transducer is a finite-state automaton with an input and an output. We consider the possibilities of probabilistic and frequency transducers and prove sever…

Discrete mathematicsAverage-case complexityAlgorithmic information theoryTheoryofComputation_COMPUTATIONBYABSTRACTDEVICESKolmogorov complexityDescriptive complexity theoryComputational physicsStructural complexity theoryTheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGESDeterministic finite automatonAsymptotic computational complexityComputer Science::Formal Languages and Automata TheoryComputational number theoryMathematics
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