Search results for "dimensionality"

showing 10 items of 231 documents

Building up adjusted indicators of students' evaluation of university courses using generalized item response models

2012

This article advances a proposal for building up adjusted composite indicators of the quality of university courses from students’ assessments. The flexible framework of Generalized Item Response Models is adopted here for controlling the sources of heterogeneity in the data structure that make evaluations across courses not directly comparable. Specifically, it allows us to: jointly model students’ ratings to the set of items which define the quality of university courses; explicitly consider the dimensionality of the items composing the evaluation form; evaluate and remove the effect of potential confounding factors which may affect students’ evaluation; model the intra-cluster variabilit…

Statistics and ProbabilityStructure (mathematical logic)Computer sciencemedia_common.quotation_subjectadjusted indicators explanatory item response models multidimensional latent traits multilevel models evaluation of university courses potential confounding factorsRegression analysisData structureAffect (psychology)Multilevel dataComputingMilieux_COMPUTERSANDEDUCATIONEconometricsMathematics educationQuality (business)Settore SECS-S/05 - Statistica SocialeStatistics Probability and UncertaintySet (psychology)Settore SECS-S/01 - Statisticamedia_commonCurse of dimensionality
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cglasso: An R Package for Conditional Graphical Lasso Inference with Censored and Missing Values

2023

Sparse graphical models have revolutionized multivariate inference. With the advent of high-dimensional multivariate data in many applied fields, these methods are able to detect a much lower-dimensional structure, often represented via a sparse conditional independence graph. There have been numerous extensions of such methods in the past decade. Many practical applications have additional covariates or suffer from missing or censored data. Despite the development of these extensions of sparse inference methods for graphical models, there have been so far no implementations for, e.g., conditional graphical models. Here we present the general-purpose package cglasso for estimating sparse co…

Statistics and Probabilityconditional Gaussian graphical modelscglasso conditional Gaussian graphical models glasso high-dimensionality sparsity censoring missing dataglassosparsityhigh-dimensionalityconditional Gaussian graphical models glasso high-dimensionality sparsity censoring missing datacglassomissing datacensoringStatistics Probability and UncertaintySettore SECS-S/01 - StatisticaSoftware
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A semiparametric approach to estimate reference curves for biophysical properties of the skin

2006

Reference curves which take one covariable into account such as the age, are often required in medicine, but simple systematic and efficient statistical methods for constructing them are lacking. Classical methods are based on parametric fitting (polynomial curves). In this chapter, we describe a new methodology for the estimation of reference curves for data sets, based on nonparametric estimation of conditional quantiles. The derived method should be applicable to all clinical or more generally biological variables that are measured on a continuous quantitative scale. To avoid the curse of dimensionality when the covariate is multidimensional, a new semiparametric approach is proposed. Th…

Statistics::TheoryKernel density estimationcomputer.software_genre01 natural sciences010104 statistics & probability0502 economics and businessCovariateSliced inverse regressionApplied mathematicsStatistics::MethodologySemiparametric regression0101 mathematics[SHS.ECO] Humanities and Social Sciences/Economics and Finance050205 econometrics MathematicsParametric statisticsDimensionality reduction05 social sciencesNonparametric statistics[ SDV.SPEE ] Life Sciences [q-bio]/Santé publique et épidémiologie[SHS.ECO]Humanities and Social Sciences/Economics and Finance3. Good health[SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologieC140;C630Data miningcomputerQuantile
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Self-Assembly of Zr(C2O4)44– Metallotectons and Bisimidazolium Cations: Influence of the Dication on H-Bonded Framework Dimensionality and Material P…

2011

Assemblies involving [Zr(C2O4)4]4– metallotectons (C2O42– = oxalate) and linear, flexible, or V-shaped organic cations (H2-Lx)2+ derived from the 1,4-bisimidazol-1-ylbenzene molecule have been envisioned to elaborate porous frameworks based on ionic H-bonds. Five architectures of formula [{(H2-L1)2Zr(C2O4)4}·2H2O] (1), [{(H2-L2)2Zr(C2O4)4}·6H2O] (2), [{(H2-L3)2Zr(C2O4)4}·6H2O] (3), [{(H2-L4)2Zr(C2O4)4}·H2O] (4), and [{(H2-L5)2Zr(C2O4)4}·6H2O] (5) (with L1 = p-bis(imidazol-1-yl)benzene, L2 = p-bis(2-methylimidazol-1-yl)benzene, L3 = p-bis(imidazol-1-yl)-2,5-dimethylbenzene, L4 = p-bis(imidazol-1-ylmethyl)benzene, L5 = m-bis(imidazol-1-yl)benzene) have been obtained; 1–3, and 5 show an open-f…

StereochemistryIonic bondingGeneral ChemistryCondensed Matter PhysicsOxalateDicationchemistry.chemical_compoundCrystallographychemistryMoleculeGeneral Materials ScienceSelf-assemblyBenzenePorosityCurse of dimensionalityCrystal Growth & Design
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The Importance of Electronic Dimensionality in Multiorbital Radical Conductors.

2019

The exceptional performance of oxobenzene-bridged bis-1,2,3-dithiazolyls 6 as single-component neutral radical conductors arises from the presence of a low-lying π-lowest unoccupied molecular orbital, which reduces the potential barrier to charge transport and increases the kinetic stabilization energy of the metallic state. As part of ongoing efforts to modify the solid-state structures and transport properties of these so-called multiorbital materials, we report the preparation and characterization of the acetoxy, methoxy, and thiomethyl derivatives 6 (R = OAc, OMe, SMe). The crystal structures are based on ribbonlike arrays of radicals laced together by S···N' and S···O' secondary bondin…

Steric effects010405 organic chemistryChemistryRadicalElectronic structureCrystal structuremultiorbital radical conductors010402 general chemistryvapaat radikaalitkiteet01 natural sciencessähkönjohtavuus0104 chemical sciencesInorganic ChemistryCrystallographyelectronic dimensionalityElectronic effectAntiferromagnetismMolecular orbitalDensity functional theoryPhysical and Theoretical Chemistryta116Inorganic chemistry
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Ligand effects on the dimensionality of oxamato-bridged mixed-metal open-framework magnets

2012

Increasing dimensionality [from 2D (1) to 3D (2)] and T(C) [from 10 (1) to 20 K (2)] in two new oxamato-bridged heterobimetallic Mn(II)(2)Cu(II)(3) open-frameworks result from the steric hindrance provided by the different alkyl substituents of the N-phenyloxamate bridging ligands.

Steric effectschemistry.chemical_classificationBridging (networking)Mixed metalChemistryLigandStereochemistryMetals and AlloysGeneral ChemistryOpen frameworkCatalysisSurfaces Coatings and FilmsElectronic Optical and Magnetic MaterialsCrystallographyMagnetMaterials ChemistryCeramics and CompositesAlkylCurse of dimensionalityChemical Communications
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A Differential Evolution Framework with Ensemble of Parameters and Strategies and Pool of Local Search Algorithms

2014

The file attached to this record is the author's final peer reviewed version. The publisher's final version can be found by following the DOI link. The ensemble structure is a computational intelligence supervised strategy consisting of a pool of multiple operators that compete among each other for being selected, and an adaptation mechanism that tends to reward the most successful operators. In this paper we extend the idea of the ensemble to multiple local search logics. In a memetic fashion, the search structure of an ensemble framework cooperatively/competitively optimizes the problem jointly with a pool of diverse local search algorithms. In this way, the algorithm progressively adapts…

Structure (mathematical logic)Theoretical computer sciencebusiness.industryComputer scienceMeta-heuristicsComputational intelligenceAdaptive algorithmsDifferential evolutionLocal search (optimization)OptimisationDifferential evolutionAdaptation (computer science)businessGlobal optimizationAlgorithmMetaheuristicEnsembleMemetic ComputingCurse of dimensionality
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Enhanced superconductivity in atomically thin TaS2

2016

The ability to exfoliate layered materials down to the single layer limit has presented the opportunity to understand how a gradual reduction in dimensionality affects the properties of bulk materials. Here we use this top–down approach to address the problem of superconductivity in the two-dimensional limit. The transport properties of electronic devices based on 2H tantalum disulfide flakes of different thicknesses are presented. We observe that superconductivity persists down to the thinnest layer investigated (3.5 nm), and interestingly, we find a pronounced enhancement in the critical temperature from 0.5 to 2.2 K as the layers are thinned down. In addition, we propose a tight-binding …

SuperconductivityWork (thermodynamics)Materials scienceScienceTantalumFOS: Physical sciencesGeneral Physics and Astronomychemistry.chemical_element02 engineering and technology01 natural sciencesArticleGeneral Biochemistry Genetics and Molecular BiologySuperconductivity (cond-mat.supr-con)Mesoscale and Nanoscale Physics (cond-mat.mes-hall)0103 physical sciences010306 general physicsSuperconductivitatSuperconductivityCoupling constantMultidisciplinaryCondensed Matter - Mesoscale and Nanoscale PhysicsAtomically thinCondensed matter physicsCondensed Matter - SuperconductivityQDisulfide bondFísicaGeneral ChemistryCiència dels materials021001 nanoscience & nanotechnologychemistry0210 nano-technologyLayer (electronics)Single layerCurse of dimensionality
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The Hierarchical Continuous Pursuit Learning Automation: A Novel Scheme for Environments With Large Numbers of Actions.

2019

Although the field of learning automata (LA) has made significant progress in the past four decades, the LA-based methods to tackle problems involving environments with a large number of actions is, in reality, relatively unresolved. The extension of the traditional LA to problems within this domain cannot be easily established when the number of actions is very large. This is because the dimensionality of the action probability vector is correspondingly large, and so, most components of the vector will soon have values that are smaller than the machine accuracy permits, implying that they will never be chosen . This paper presents a solution that extends the continuous pursuit paradigm to …

Theoretical computer scienceHierarchical learning automataHierarchy (mathematics)DiscretizationLearning automataComputer Networks and CommunicationsComputer scienceLarge action numbersPursuit learning automata02 engineering and technologyVDP::Matematikk og Naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420Probability vectorLearning automataComputer Science ApplicationsAutomatonOperator (computer programming)Artificial Intelligence0202 electrical engineering electronic engineering information engineeringBenchmark (computing)Estimator-based learning automata020201 artificial intelligence & image processingVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550SoftwareCurse of dimensionalityIEEE transactions on neural networks and learning systems
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The Hierarchical Continuous Pursuit Learning Automation for Large Numbers of Actions

2018

Part 10: Learning - Intelligence; International audience; Although the field of Learning Automata (LA) has made significant progress in the last four decades, the LA-based methods to tackle problems involving environments with a large number of actions are, in reality, relatively unresolved. The extension of the traditional LA (fixed structure, variable structure, discretized, and pursuit) to problems within this domain cannot be easily established when the number of actions is very large. This is because the dimensionality of the action probability vector is correspondingly large, and consequently, most components of the vector will, after a relatively short time, have values that are smal…

Theoretical computer scienceHierarchical learning automataHierarchy (mathematics)Learning automataComputer sciencePursuit learning automataPursuit LALearning Automata02 engineering and technologyEstimator-based LAProbability vectorField (computer science)020202 computer hardware & architectureLA with large number of actionsVariable (computer science)Operator (computer programming)Learning Automata (LA)Action (philosophy)0202 electrical engineering electronic engineering information engineeringEstimator-based learning automata[INFO]Computer Science [cs]020201 artificial intelligence & image processingHierarchical LACurse of dimensionality
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