Search results for "statistical"

showing 10 items of 4960 documents

Exact quantum algorithms have advantage for almost all Boolean functions

2014

It has been proved that almost all $n$-bit Boolean functions have exact classical query complexity $n$. However, the situation seemed to be very different when we deal with exact quantum query complexity. In this paper, we prove that almost all $n$-bit Boolean functions can be computed by an exact quantum algorithm with less than $n$ queries. More exactly, we prove that ${AND}_n$ is the only $n$-bit Boolean function, up to isomorphism, that requires $n$ queries.

FOS: Computer and information sciencesNuclear and High Energy Physics81P68 03D15Parity functionBoolean circuitGeneral Physics and AstronomyFOS: Physical sciencesBoolean algebras canonically definedComputational Complexity (cs.CC)Theoretical Computer ScienceCombinatoricsBoolean expressionBoolean functionMathematical PhysicsComputer Science::DatabasesMathematicsDiscrete mathematicsSymmetric Boolean functionQuantum PhysicsProduct termComputer Science::Information RetrievalStatistical and Nonlinear PhysicsComputer Science - Computational ComplexityComputational Theory and MathematicsMaximum satisfiability problemQuantum Physics (quant-ph)
researchProduct

Quantum lower bound for inverting a permutation with advice

2014

Given a random permutation $f: [N] \to [N]$ as a black box and $y \in [N]$, we want to output $x = f^{-1}(y)$. Supplementary to our input, we are given classical advice in the form of a pre-computed data structure; this advice can depend on the permutation but \emph{not} on the input $y$. Classically, there is a data structure of size $\tilde{O}(S)$ and an algorithm that with the help of the data structure, given $f(x)$, can invert $f$ in time $\tilde{O}(T)$, for every choice of parameters $S$, $T$, such that $S\cdot T \ge N$. We prove a quantum lower bound of $T^2\cdot S \ge \tilde{\Omega}(\epsilon N)$ for quantum algorithms that invert a random permutation $f$ on an $\epsilon$ fraction of…

FOS: Computer and information sciencesNuclear and High Energy PhysicsComputer Science - Cryptography and SecurityGeneral Physics and AstronomyFOS: Physical sciencesOne-way functionComputational Complexity (cs.CC)Upper and lower boundsTheoretical Computer ScienceCyclic permutationCombinatoricsPermutationMathematical PhysicsMathematicsDiscrete mathematicsQuantum PhysicsBit-reversal permutationStatistical and Nonlinear PhysicsRandom permutationComputer Science - Computational ComplexityComputational Theory and MathematicsQuantum algorithmQuantum Physics (quant-ph)Advice (complexity)Cryptography and Security (cs.CR)MathematicsofComputing_DISCRETEMATHEMATICS
researchProduct

Statistically validated mobile communication networks: the evolution of motifs in European and Chinese data

2014

Big data open up unprecedented opportunities to investigate complex systems including the society. In particular, communication data serve as major sources for computational social sciences but they have to be cleaned and filtered as they may contain spurious information due to recording errors as well as interactions, like commercial and marketing activities, not directly related to the social network. The network constructed from communication data can only be considered as a proxy for the network of social relationships. Here we apply a systematic method, based on multiple hypothesis testing, to statistically validate the links and then construct the corresponding Bonferroni network, gen…

FOS: Computer and information sciencesPhysics - Physics and SocietyBig dataFOS: Physical sciencesGeneral Physics and AstronomyPhysics and Society (physics.soc-ph)computer.software_genre01 natural sciences010305 fluids & plasmassymbols.namesake0103 physical sciences010306 general physicsProxy (statistics)Social and Information Networks (cs.SI)PhysicsSocial networkbusiness.industryComputer Science - Social and Information NetworksComplex networkcomplex networks social systems statistically validated networks mobile call records 3-motifsSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Bonferroni correctionMobile phonesymbolsMobile telephonyData miningRaw databusinesscomputer
researchProduct

A comparative analysis of the statistical properties of large mobile phone calling networks.

2014

Mobile phone calling is one of the most widely used communication methods in modern society. The records of calls among mobile phone users provide us a valuable proxy for the understanding of human communication patterns embedded in social networks. Mobile phone users call each other forming a directed calling network. If only reciprocal calls are considered, we obtain an undirected mutual calling network. The preferential communication behavior between two connected users can be statistically tested and it results in two Bonferroni networks with statistically validated edges. We perform a comparative analysis of the statistical properties of these four networks, which are constructed from …

FOS: Computer and information sciencesPhysics - Physics and SocietyChinaComputer scienceFOS: Physical sciencesInformation Storage and RetrievalPhysics and Society (physics.soc-ph)ArticleSocial NetworkingComputer Communication NetworksSocio-technical systemsComputer SimulationProxy (statistics)Human communicationStatisticSocial and Information Networks (cs.SI)MultidisciplinaryModels StatisticalSocial networkbusiness.industryStatistical physicComputer Science - Social and Information NetworksNonlinear phenomenaComplex networkSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Mobile phonebusinessTelecommunicationsCell PhoneScientific reports
researchProduct

Epidemic spreading and aging in temporal networks with memory

2018

Time-varying network topologies can deeply influence dynamical processes mediated by them. Memory effects in the pattern of interactions among individuals are also known to affect how diffusive and spreading phenomena take place. In this paper we analyze the combined effect of these two ingredients on epidemic dynamics on networks. We study the susceptible-infected-susceptible (SIS) and the susceptible-infected-removed (SIR) models on the recently introduced activity-driven networks with memory. By means of an activity-based mean-field approach we derive, in the long time limit, analytical predictions for the epidemic threshold as a function of the parameters describing the distribution of …

FOS: Computer and information sciencesPhysics - Physics and SocietyComputer scienceAnalytical predictionsEpidemic dynamicsFOS: Physical sciencesPhysics and Society (physics.soc-ph)Network topology01 natural sciences010305 fluids & plasmasNetworks and Complex Systems0103 physical sciencesQuantitative Biology::Populations and EvolutionStatistical physicsLimit (mathematics)010306 general physicsQuantitative Biology - Populations and EvolutionEpidemic controlSocial and Information Networks (cs.SI)Populations and Evolution (q-bio.PE)Computer Science - Social and Information NetworksFunction (mathematics)Computer Science::Social and Information NetworksArticlesDynamic modelsEpidemic thresholdEpidemic spreadingFOS: Biological sciencesMean field approachPhysical Review. E
researchProduct

Detecting informative higher-order interactions in statistically validated hypergraphs

2021

Recent empirical evidence has shown that in many real-world systems, successfully represented as networks, interactions are not limited to dyads, but often involve three or more agents at a time. These data are better described by hypergraphs, where hyperlinks encode higher-order interactions among a group of nodes. In spite of the large number of works on networks, highlighting informative hyperlinks in hypergraphs obtained from real world data is still an open problem. Here we propose an analytic approach to filter hypergraphs by identifying those hyperlinks that are over-expressed with respect to a random null hypothesis, and represent the most relevant higher-order connections. We apply…

FOS: Computer and information sciencesPhysics - Physics and SocietyComputer scienceQC1-999Open problemFOS: Physical sciencesGeneral Physics and AstronomyPhysics and Society (physics.soc-ph)Astrophysicscomputer.software_genreENCODEMethodology (stat.ME)Statistics - MethodologySocial and Information Networks (cs.SI)PhysicsComputer Science - Social and Information NetworksFilter (signal processing)HyperlinkClass (biology)Settore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)QB460-466Pairwise comparisonData miningNoise (video)Null hypothesiscomputerhigher order interactions statistical validation complex networksCommunications Physics
researchProduct

Classical and Quantum Annealing in the Median of Three Satisfiability

2011

We determine the classical and quantum complexities of a specific ensemble of three-satisfiability problems with a unique satisfying assignment for up to N = 100 and 80 variables, respectively. In the classical limit, we employ generalized ensemble techniques and measure the time that a Markovian Monte Carlo process spends in searching classical ground states. In the quantum limit, we determine the maximum finite correlation length along a quantum adiabatic trajectory determined by the linear sweep of the adiabatic control parameter in the Hamiltonian composed of the problem Hamiltonian and the constant transverse field Hamiltonian. In the median of our ensemble, both complexities diverge e…

FOS: Computer and information sciencesPolynomialComputational complexity theoryQuantum dynamicsFOS: Physical sciencesComputational Complexity (cs.CC)Classical limitClassical capacityQuantum mechanicsddc:530Statistical physicsALGORITHMAmplitude damping channelQuantumQuantum fluctuationCondensed Matter - Statistical MechanicsMathematicsPhysicsQuantum PhysicsStatistical Mechanics (cond-mat.stat-mech)Stochastic processQuantum annealingAdiabatic quantum computationAtomic and Molecular Physics and OpticsSatisfiabilityJComputer Science - Computational ComplexityComputerSystemsOrganization_MISCELLANEOUSQuantum algorithmPHASE-TRANSITIONSQuantum dissipationQuantum Physics (quant-ph)
researchProduct

PRINCIPAL POLYNOMIAL ANALYSIS

2014

© 2014 World Scientific Publishing Company. This paper presents a new framework for manifold learning based on a sequence of principal polynomials that capture the possibly nonlinear nature of the data. The proposed Principal Polynomial Analysis (PPA) generalizes PCA by modeling the directions of maximal variance by means of curves instead of straight lines. Contrarily to previous approaches PPA reduces to performing simple univariate regressions which makes it computationally feasible and robust. Moreover PPA shows a number of interesting analytical properties. First PPA is a volume preserving map which in turn guarantees the existence of the inverse. Second such an inverse can be obtained…

FOS: Computer and information sciencesPolynomialComputer Networks and CommunicationsComputer scienceMachine Learning (stat.ML)02 engineering and technologyReduction (complexity)03 medical and health sciencessymbols.namesake0302 clinical medicineStatistics - Machine LearningArtificial Intelligence0202 electrical engineering electronic engineering information engineeringPrincipal Polynomial AnalysisPrincipal Component AnalysisMahalanobis distanceModels StatisticalCodingDimensionality reductionNonlinear dimensionality reductionGeneral MedicineClassificationDimensionality reductionManifold learningNonlinear DynamicsMetric (mathematics)Jacobian matrix and determinantsymbolsRegression Analysis020201 artificial intelligence & image processingNeural Networks ComputerAlgorithmAlgorithms030217 neurology & neurosurgeryCurse of dimensionalityInternational Journal of Neural Systems
researchProduct

Probabilistic Memristive Networks: Application of a Master Equation to Networks of Binary ReRAM cells

2020

Abstract The possibility of using non-deterministic circuit components has been gaining significant attention in recent years. The modeling and simulation of their circuits require novel approaches, as now the state of a circuit at an arbitrary moment in time cannot be predicted deterministically. Generally, these circuits should be described in terms of probabilities, the circuit variables should be calculated on average, and correlation functions should be used to explore interrelations among the variables. In this paper, we use, for the first time, a master equation to analyze the networks composed of probabilistic binary memristors. Analytical solutions of the master equation for the ca…

FOS: Computer and information sciencesProbabilistic computingComputer scienceGeneral MathematicsGeneral Physics and AstronomyBinary numberFOS: Physical sciencesComputer Science - Emerging TechnologiesMemristorTopologylaw.inventionModeling and simulationComputer Science::Hardware ArchitectureComputer Science::Emerging TechnologieslawMaster equationMesoscale and Nanoscale Physics (cond-mat.mes-hall)Probabilistic logicElectronic circuitCondensed Matter - Materials ScienceCondensed Matter - Mesoscale and Nanoscale PhysicsApplied MathematicsProbabilistic logicMaterials Science (cond-mat.mtrl-sci)Statistical and Nonlinear PhysicsMoment (mathematics)Emerging Technologies (cs.ET)State (computer science)NetworksMemristors
researchProduct

Corrigendum: ExGUtils: A Python Package for Statistical Analysis With the ex-Gaussian Probability Density

2018

The study of reaction times and their underlying cognitive processes is an important field in Psychology. Reaction times are usually modeled through the ex-Gaussian distribution, because it provides a good fit to multiple empirical data. The complexity of this distribution makes the use of computational tools an essential element in the field. Therefore, there is a strong need for efficient and versatile computational tools for the research in this area. In this manuscript we discuss some mathematical details of the ex-Gaussian distribution and apply the ExGUtils package, a set of functions and numerical tools, programmed for python, developed for numerical analysis of data involving the ex…

FOS: Computer and information sciencesResponse timeslcsh:BF1-990Probability density functionex-Gaussian fitStatistics - Applications050105 experimental psychology03 medical and health sciences0302 clinical medicineSignificance testingresponse componentsConceptual AnalysisPsychology0501 psychology and cognitive sciencesStatistical analysisApplications (stat.AP)Ex-Gaussian fitTempo de reaçãoGeneral Psychologycomputer.programming_languagesignificance testingResponse componentsNumerical analysis05 social sciencesAnálise estatísticaCorrectionPython (programming language)Ex gaussianDistribuição Gaussianapythonlcsh:PsychologyOutlierTrimmingPsychologyMATEMATICA APLICADAAlgorithmcomputerSignificance testing030217 neurology & neurosurgeryresponse timesPython
researchProduct