Search results for "FOS: Mathematics"

showing 10 items of 1448 documents

Array programming with NumPy.

2020

Array programming provides a powerful, compact and expressive syntax for accessing, manipulating and operating on data in vectors, matrices and higher-dimensional arrays. NumPy is the primary array programming library for the Python language. It has an essential role in research analysis pipelines in fields as diverse as physics, chemistry, astronomy, geoscience, biology, psychology, materials science, engineering, finance and economics. For example, in astronomy, NumPy was an important part of the software stack used in the discovery of gravitational waves1 and in the first imaging of a black hole2. Here we review how a few fundamental array concepts lead to a simple and powerful programmi…

FOS: Computer and information sciences/639/705/1042Computer science/639/705/794Interoperability/639/705/117Review ArticleStatistics - Computationohjelmointikielet01 natural sciences03 medical and health sciencesSoftwareSoftware Designlaskennallinen tiede0103 physical sciencesFOS: Mathematics010303 astronomy & astrophysicsComputation (stat.CO)030304 developmental biologycomputer.programming_languageSolar physics0303 health sciencesMultidisciplinaryApplication programming interfacebusiness.industryNumPyComputational sciencereview-articleComputational BiologyPython (programming language)Computer science/704/525/870Computational neuroscienceProgramming paradigmSoftware designComputer Science - Mathematical Software/631/378/116/139Programming LanguagesArray programmingohjelmistokirjastotSoftware engineeringbusinessMathematical Software (cs.MS)computerMathematicsSoftwarePythonNature
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On the interpretability and computational reliability of frequency-domain Granger causality

2017

This Correspondence article is a comment which directly relates to the paper “A study of problems encountered in Granger causality analysis from a neuroscience perspective” (Stokes and Purdon, 2017). We agree that interpretation issues of Granger causality (GC) in neuroscience exist, partially due to the historically unfortunate use of the name “causality”, as described in previous literature. On the other hand, we think that Stokes and Purdon use a formulation of GC which is outdated (albeit still used) and do not fully account for the potential of the different frequency-domain versions of GC; in doing so, their paper dismisses GC measures based on a suboptimal use of them. Furthermore, s…

FOS: Computer and information sciences0301 basic medicineTheoretical computer scienceImmunology and Microbiology (all)Computer scienceTime series analysiMathematics - Statistics TheoryStatistics Theory (math.ST)Statistics - ApplicationsGeneral Biochemistry Genetics and Molecular BiologyMethodology (stat.ME)Causality (physics)03 medical and health sciences0302 clinical medicinegranger causalityGranger causalityCorrespondenceFOS: MathematicsApplications (stat.AP)Physiological oscillationGeneral Pharmacology Toxicology and PharmaceuticsTime seriessignal processingStatistical Methodologies & Health Informaticsfrequency-domain connectivityReliability (statistics)Statistics - MethodologyInterpretabilityGranger-Geweke causalityBiochemistry Genetics and Molecular Biology (all)Interpretation (logic)General Immunology and Microbiologybrain connectivityGeneral MedicineArticlesvector autoregressive models030104 developmental biologyMathematics and StatisticsWildcardVector autoregressive modelPharmacology Toxicology and Pharmaceutics (all)Frequency domaintime series analysisspectral decompositionSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaBrain connectivity; Directed coherence; Frequency-domain connectivity; Granger-Geweke causality; Physiological oscillations; Spectral decomposition; Time series analysis; Vector autoregressive models; Biochemistry Genetics and Molecular Biology (all); Immunology and Microbiology (all); Pharmacology Toxicology and Pharmaceutics (all)directed coherence030217 neurology & neurosurgeryphysiological oscillations
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On the Inner Product Predicate and a Generalization of Matching Vector Families

2018

Motivated by cryptographic applications such as predicate encryption, we consider the problem of representing an arbitrary predicate as the inner product predicate on two vectors. Concretely, fix a Boolean function $P$ and some modulus $q$. We are interested in encoding $x$ to $\vec x$ and $y$ to $\vec y$ so that $$P(x,y) = 1 \Longleftrightarrow \langle\vec x,\vec y\rangle= 0 \bmod q,$$ where the vectors should be as short as possible. This problem can also be viewed as a generalization of matching vector families, which corresponds to the equality predicate. Matching vector families have been used in the constructions of Ramsey graphs, private information retrieval (PIR) protocols, and mor…

FOS: Computer and information sciences060201 languages & linguistics000 Computer science knowledge general worksComputer Science - Cryptography and Security06 humanities and the arts02 engineering and technologyComputational Complexity (cs.CC)Computer Science - Computational Complexity0602 languages and literatureComputer ScienceFOS: Mathematics0202 electrical engineering electronic engineering information engineeringMathematics - Combinatorics020201 artificial intelligence & image processingCombinatorics (math.CO)Cryptography and Security (cs.CR)
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Combinatorial proofs of two theorems of Lutz and Stull

2021

Recently, Lutz and Stull used methods from algorithmic information theory to prove two new Marstrand-type projection theorems, concerning subsets of Euclidean space which are not assumed to be Borel, or even analytic. One of the theorems states that if $K \subset \mathbb{R}^{n}$ is any set with equal Hausdorff and packing dimensions, then $$ \dim_{\mathrm{H}} π_{e}(K) = \min\{\dim_{\mathrm{H}} K,1\} $$ for almost every $e \in S^{n - 1}$. Here $π_{e}$ stands for orthogonal projection to $\mathrm{span}(e)$. The primary purpose of this paper is to present proofs for Lutz and Stull's projection theorems which do not refer to information theoretic concepts. Instead, they will rely on combinatori…

FOS: Computer and information sciences28A80 (primary) 28A78 (secondary)General MathematicskombinatoriikkaCombinatorial proofComputational Complexity (cs.CC)01 natural sciencesCombinatoricsMathematics - Metric GeometryHausdorff and packing measures0103 physical sciencesClassical Analysis and ODEs (math.CA)FOS: Mathematics0101 mathematicsMathematicsAlgorithmic information theoryLemma (mathematics)Euclidean spacePigeonhole principle010102 general mathematicsOrthographic projectionHausdorff spaceMetric Geometry (math.MG)Projection (relational algebra)Computer Science - Computational ComplexityMathematics - Classical Analysis and ODEsfraktaalit010307 mathematical physicsmittateoria
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Selectivity in Probabilistic Causality: Drawing Arrows from Inputs to Stochastic Outputs

2011

Given a set of several inputs into a system (e.g., independent variables characterizing stimuli) and a set of several stochastically non-independent outputs (e.g., random variables describing different aspects of responses), how can one determine, for each of the outputs, which of the inputs it is influenced by? The problem has applications ranging from modeling pairwise comparisons to reconstructing mental processing architectures to conjoint testing. A necessary and sufficient condition for a given pattern of selective influences is provided by the Joint Distribution Criterion, according to which the problem of "what influences what" is equivalent to that of the existence of a joint distr…

FOS: Computer and information sciencesArtificial Intelligence (cs.AI)91E45 (Primary) 60A05 (Secondary)Computer Science - Artificial IntelligencePhysics - Data Analysis Statistics and ProbabilityFOS: Biological sciencesProbability (math.PR)FOS: MathematicsFOS: Physical sciencesQuantitative Biology - Quantitative MethodsMathematics - ProbabilityData Analysis Statistics and Probability (physics.data-an)Quantitative Methods (q-bio.QM)
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Popularity of patterns over $d$-equivalence classes of words and permutations

2020

Abstract Two same length words are d-equivalent if they have same descent set and same underlying alphabet. In particular, two same length permutations are d-equivalent if they have same descent set. The popularity of a pattern in a set of words is the overall number of copies of the pattern within the words of the set. We show the far-from-trivial fact that two patterns are d-equivalent if and only if they are equipopular over any d-equivalence class, and this equipopularity does not follow obviously from a trivial equidistribution.

FOS: Computer and information sciencesClass (set theory)General Computer ScienceDiscrete Mathematics (cs.DM)010102 general mathematics0102 computer and information sciences01 natural sciencesPopularityTheoretical Computer ScienceCombinatoricsSet (abstract data type)010201 computation theory & mathematicsIf and only if[MATH.MATH-CO]Mathematics [math]/Combinatorics [math.CO]FOS: MathematicsMathematics - CombinatoricsCombinatorics (math.CO)0101 mathematicsAlphabetComputingMilieux_MISCELLANEOUSComputer Science::Formal Languages and Automata TheoryMathematicsDescent (mathematics)Computer Science - Discrete Mathematics
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Probabilistic entailment in the setting of coherence: The role of quasi conjunction and inclusion relation

2013

In this paper, by adopting a coherence-based probabilistic approach to default reasoning, we focus the study on the logical operation of quasi conjunction and the Goodman-Nguyen inclusion relation for conditional events. We recall that quasi conjunction is a basic notion for defining consistency of conditional knowledge bases. By deepening some results given in a previous paper we show that, given any finite family of conditional events F and any nonempty subset S of F, the family F p-entails the quasi conjunction C(S); then, given any conditional event E|H, we analyze the equivalence between p-entailment of E|H from F and p-entailment of E|H from C(S), where S is some nonempty subset of F.…

FOS: Computer and information sciencesClass (set theory)Goodman–Nguyen’s inclusion relationQAND ruleSettore MAT/06 - Probabilita' E Statistica MatematicaComputer Science - Artificial IntelligenceMathematics - Statistics TheoryStatistics Theory (math.ST)Logical consequencegoodman-nguyen's inclusion relationTheoretical Computer ScienceArtificial IntelligenceQuasi conjunctionFOS: MathematicsEquivalence (measure theory)MathematicsEvent (probability theory)Discrete mathematicsSettore INF/01 - InformaticaApplied MathematicsProbability (math.PR)quasi conjunction; goodman-nguyen inclusion relation; qand rule; coherence; probabilistic default reasoning; p-entailment; goodman-nguyen's inclusion relationProbabilistic logicCoherence (statistics)Conjunction (grammar)Greatest elementArtificial Intelligence (cs.AI)Probabilistic default reasoninggoodman-nguyen inclusion relationp-EntailmentCoherenceSoftwareMathematics - Probability
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On the Number of Closed Factors in a Word

2015

A closed word (a.k.a. periodic-like word or complete first return) is a word whose longest border does not have internal occurrences, or, equivalently, whose longest repeated prefix is not right special. We investigate the structure of closed factors of words. We show that a word of length $n$ contains at least $n+1$ distinct closed factors, and characterize those words having exactly $n+1$ closed factors. Furthermore, we show that a word of length $n$ can contain $\Theta(n^{2})$ many distinct closed factors.

FOS: Computer and information sciencesClosed wordCombinatorics on wordsComplete returnFormal Languages and Automata Theory (cs.FL)Computer scienceComputer Science (all)Structure (category theory)Computer Science - Formal Languages and Automata TheoryCombinatorics on words Closed word Complete return Rich word Bitonic word68R15Theoretical Computer ScienceCombinatoricsPrefixCombinatorics on wordsRich wordBitonic wordFOS: MathematicsMathematics - CombinatoricsCombinatorics (math.CO)ArithmeticWord (computer architecture)Combinatorics on word
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Uncommon Suffix Tries

2011

Common assumptions on the source producing the words inserted in a suffix trie with $n$ leaves lead to a $\log n$ height and saturation level. We provide an example of a suffix trie whose height increases faster than a power of $n$ and another one whose saturation level is negligible with respect to $\log n$. Both are built from VLMC (Variable Length Markov Chain) probabilistic sources; they are easily extended to families of sources having the same properties. The first example corresponds to a ''logarithmic infinite comb'' and enjoys a non uniform polynomial mixing. The second one corresponds to a ''factorial infinite comb'' for which mixing is uniform and exponential.

FOS: Computer and information sciencesCompressed suffix arrayPolynomialLogarithmGeneral MathematicsSuffix treevariable length Markov chain[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS]Generalized suffix treeprobabilistic source0102 computer and information sciences02 engineering and technologysuffix trie01 natural scienceslaw.inventionCombinatoricslawComputer Science - Data Structures and AlgorithmsTrieFOS: Mathematics0202 electrical engineering electronic engineering information engineeringData Structures and Algorithms (cs.DS)Mixing (physics)[ INFO.INFO-DS ] Computer Science [cs]/Data Structures and Algorithms [cs.DS]MathematicsDiscrete mathematicsApplied MathematicsProbability (math.PR)020206 networking & telecommunicationssuffix trie.Computer Graphics and Computer-Aided Design[MATH.MATH-PR]Mathematics [math]/Probability [math.PR]010201 computation theory & mathematicsmixing properties60J05 37E05Suffix[ MATH.MATH-PR ] Mathematics [math]/Probability [math.PR]Mathematics - ProbabilitySoftware
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Inductive types in homotopy type theory

2012

Homotopy type theory is an interpretation of Martin-L\"of's constructive type theory into abstract homotopy theory. There results a link between constructive mathematics and algebraic topology, providing topological semantics for intensional systems of type theory as well as a computational approach to algebraic topology via type theory-based proof assistants such as Coq. The present work investigates inductive types in this setting. Modified rules for inductive types, including types of well-founded trees, or W-types, are presented, and the basic homotopical semantics of such types are determined. Proofs of all results have been formally verified by the Coq proof assistant, and the proof s…

FOS: Computer and information sciencesComputer Science - Logic in Computer Science03B15 03B70 03F500102 computer and information sciences01 natural sciencesComputer Science::Logic in Computer ScienceFOS: MathematicsA¹ homotopy theoryCategory Theory (math.CT)0101 mathematicsMathematicsHomotopy lifting propertyType theory inductive types homotopy-initial algebraHomotopy010102 general mathematicsMathematics - Category TheoryIntuitionistic type theoryMathematics - LogicSettore MAT/01 - Logica MatematicaLogic in Computer Science (cs.LO)Algebran-connectedType theoryTheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGES010201 computation theory & mathematicsProof theoryTheoryofComputation_LOGICSANDMEANINGSOFPROGRAMSHomotopy type theoryComputer Science::Programming LanguagesLogic (math.LO)
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