Search results for "Probability."

showing 10 items of 3396 documents

A novel Bayesian framework for relevance feedback in image content-based retrieval systems

2006

This paper presents a new algorithm for image retrieval in content-based image retrieval systems. The objective of these systems is to get the images which are as similar as possible to a user query from those contained in the global image database without using textual annotations attached to the images. The main problem in obtaining a robust and effective retrieval is the gap between the low level descriptors that can be automatically extracted from the images and the user intention. The algorithm proposed here to address this problem is based on the modeling of user preferences as a probability distribution on the image space. Following a Bayesian methodology, this distribution is the pr…

Computer sciencebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONRelevance feedbackPattern recognitioncomputer.software_genreAutomatic image annotationArtificial IntelligenceComputer Science::Computer Vision and Pattern RecognitionSignal ProcessingProbability distributionComputer Vision and Pattern RecognitionVisual WordArtificial intelligenceData miningbusinessPrecision and recallImage retrievalcomputerSoftwarePattern Recognition
researchProduct

The Influence of LOS Components on the Statistical Properties of the Capacity of Amplify-and-Forward Channels

2009

Also available from publisher: http://dx.doi.org/10.4236/wsn.2009.11002 Amplify-and-forward channels in cooperative networks provide a promising improvement in the network coverage and system throughput. Under line-of-sight (LOS) propagation conditions in such cooperative networks, the overall fading channel can be modeled by a double Rice process. In this article, we have stud-ied the statistical properties of the capacity of double Rice fading channels. We have derived the analytical expressions for the probability density function (PDF), cumulative distribution function (CDF), level- crossing rate (LCR), and average duration of fades (ADF) of the channel capacity. The obtained results ar…

Computer sciencebusiness.industryCumulative distribution functionProbability density functionThroughputCommunications systemTopologysymbols.namesakeChannel capacityAmplitudeVDP::Technology: 500::Information and communication technology: 550::Telecommunication: 552symbolsFadingRayleigh scatteringTelecommunicationsbusinessComputer Science::Information TheoryWireless Sensor Network
researchProduct

Modeling and statistical characterization of wideband indoor radio propagation channels

2010

In this paper, we focus on the modeling of wideband single-input single-output (SISO) mobile fading channels for indoor propagation environments. The derived indoor reference channel model is based on a geometrical scattering model, which consists of an infinite number of scatterers uniformly distributed over the two-dimensional (2D) horizontal plane of a rectangular room. We derive analytical expressions for the probability density function (PDF) of the angle of arrival (AOA), the power delay profile (PDP), and the frequency correlation function (FCF). An efficient sum-of-cisoids (SOC) channel simulator will be derived from the proposed non-realizable reference model. It is shown that the …

Computer sciencebusiness.industryProbability density functionData_CODINGANDINFORMATIONTHEORYPropagation delayCorrelation function (quantum field theory)Computer Science::Hardware ArchitectureAngle of arrivalElectronic engineeringFadingWidebandTelecommunicationsbusinessPower delay profileReference modelComputer Science::Information TheoryInternational Congress on Ultra Modern Telecommunications and Control Systems
researchProduct

Listwise Recommendation Approach with Non-negative Matrix Factorization

2018

Matrix factorization (MF) is one of the most effective categories of recommendation algorithms, which makes predictions based on the user-item rating matrix. Nowadays many studies reveal that the ultimate goal of recommendations is to predict correct rankings of these unrated items. However, most of the pioneering efforts on ranking-oriented MF predict users’ item ranking based on the original rating matrix, which fails to explicitly present users’ preference ranking on items and thus might result in some accuracy loss. In this paper, we formulate a novel listwise user-ranking probability prediction problem for recommendations, that aims to utilize a user-ranking probability matrix to predi…

Computer sciencebusiness.industrysuosittelujärjestelmätStochastic matrixRecommender systemMissing dataMachine learningcomputer.software_genreMatrix decompositionNon-negative matrix factorizationMatrix (mathematics)rankingRankingcollaborative filteringalgoritmitProbability distributionArtificial intelligencebusinesscomputer
researchProduct

Hidden attractors on one path : Glukhovsky-Dolzhansky, Lorenz, and Rabinovich systems

2017

In this report, by the numerical continuation method we visualize and connect hidden chaotic sets in the Glukhovsky-Dolzhansky, Lorenz and Rabinovich systems using a certain path in the parameter space of a Lorenz-like system.

Computer sciencechaosChaoticFOS: Physical sciencesPhysics::Data Analysis; Statistics and ProbabilityParameter space01 natural sciences010305 fluids & plasmasRabinovich systemLorenz system0103 physical sciencesAttractorGlukhovsky–Dolzhansky systemApplied mathematics010301 acousticsEngineering (miscellaneous)kaaosteoriaApplied Mathematicsta111Lorenz-like systemNonlinear Sciences - Chaotic DynamicsNonlinear Sciences::Chaotic DynamicsNumerical continuationModeling and SimulationPath (graph theory)numeerinen analyysiChaotic Dynamics (nlin.CD)hidden attractorInternational Journal of Bifurcation and Chaos
researchProduct

Vectors of Pairwise Item Preferences

2019

Neural embedding has been widely applied as an effective category of vectorization methods in real-world recommender systems. However, its exploration of users’ explicit feedback on items, to create good quality user and item vectors is still limited. Existing neural embedding methods only consider the items that are accessed by the users, but neglect the scenario when a user gives high or low rating to a particular item. In this paper, we propose Pref2Vec, a method to generate vector representations of pairwise item preferences, users and items, which can be directly utilized for machine learning tasks. Specifically, Pref2Vec considers users’ pairwise item preferences as elementary units. …

Computer scienceneuraalilaskentaInitialization02 engineering and technology010501 environmental sciencesRecommender systemMachine learningcomputer.software_genre01 natural sciences0202 electrical engineering electronic engineering information engineeringvectorizationPreference (economics)Independence (probability theory)0105 earth and related environmental sciencesbusiness.industryComputer Science::Information RetrievalsuosittelujärjestelmätConditional probabilityneural embeddingVectorization (mathematics)Benchmark (computing)020201 artificial intelligence & image processingPairwise comparisonArtificial intelligencebusinesscomputer
researchProduct

Concept Drift Detection Using Online Histogram-Based Bayesian Classifiers

2016

In this paper, we present a novel algorithm that performs online histogram-based classification, i.e., specifically designed for the case when the data is dynamic and its distribution is non-stationary. Our method, called the Online Histogram-based Naïve Bayes Classifier (OHNBC) involves a statistical classifier based on the well-established Bayesian theory, but which makes some assumptions with respect to the independence of the attributes. Moreover, this classifier generates a prediction model using uni-dimensional histograms, whose segments or buckets are fixed in terms of their cardinalities but dynamic in terms of their widths. Additionally, our algorithm invokes the principles of info…

Concept driftComputer sciencebusiness.industryBayesian probabilityPattern recognition02 engineering and technologycomputer.software_genreInformation theoryNaive Bayes classifierComputingMethodologies_PATTERNRECOGNITION020204 information systemsHistogram0202 electrical engineering electronic engineering information engineeringsort020201 artificial intelligence & image processingData miningArtificial intelligencebusinesscomputerClassifier (UML)Statistical classifier
researchProduct

Online Estimation of Discrete Densities

2013

We address the problem of estimating a discrete joint density online, that is, the algorithm is only provided the current example and its current estimate. The proposed online estimator of discrete densities, EDDO (Estimation of Discrete Densities Online), uses classifier chains to model dependencies among features. Each classifier in the chain estimates the probability of one particular feature. Because a single chain may not provide a reliable estimate, we also consider ensembles of classifier chains and ensembles of weighted classifier chains. For all density estimators, we provide consistency proofs and propose algorithms to perform certain inference tasks. The empirical evaluation of t…

Concept driftStochastic processEstimation theoryBayesian probabilityEstimatorInferenceData miningClassifier chainscomputer.software_genreClassifier (UML)computerMathematics2013 IEEE 13th International Conference on Data Mining
researchProduct

Chiralities of nodal points along high symmetry lines with screw rotation symmetry

2021

Screw rotations in nonsymmorphic space group symmetries induce the presence of hourglass and accordion shape band structures along screw invariant lines whenever spin-orbit coupling is nonnegligible. These structures induce topological enforced Weyl points on the band intersections. In this work we show that the chirality of each Weyl point is related to the representations of the cyclic group on the bands that form the intersection. To achieve this, we calculate the Picard group of isomorphism classes of complex line bundles over the 2-dimensional sphere with cyclic group action, and we show how the chirality (Chern number) relates to the eigenvalues of the rotation action on the rotation …

Condensed Matter - Materials ScienceChern classComplex lineMaterials Science (cond-mat.mtrl-sci)FOS: Physical sciencesCyclic group02 engineering and technology021001 nanoscience & nanotechnologyCoupling (probability)01 natural sciences0103 physical sciencesHomogeneous spaceFOS: MathematicsAlgebraic Topology (math.AT)Equivariant mapMathematics - Algebraic TopologyInvariant (mathematics)Symmetry (geometry)010306 general physics0210 nano-technologyMathematical physics
researchProduct

Speeding up of microstructure reconstruction: II. Application to patterns of poly-dispersed islands

2015

We report a fast, efficient and credible statistical reconstruction of any two-phase patterns of islands of miscellaneous shapes and poly-dispersed in sizes. In the proposed multi-scale approach called a weighted doubly-hybrid, two different pairs of hybrid descriptors are used. As the first pair, we employ entropic quantifiers, while correlation functions are the second pair. Their competition allows considering a wider spectrum of morphological features. Instead of a standard random initial configuration, a synthetic one with the same number of islands as that of the target is created by a cellular automaton. This is the key point for speeding-up of microstructure reconstruction, making u…

Condensed Matter - Materials ScienceGeneral Computer ScienceStatistical Mechanics (cond-mat.stat-mech)Interface (Java)Computer scienceMonte Carlo methodGeneral Physics and AstronomyMaterials Science (cond-mat.mtrl-sci)FOS: Physical sciencesGeneral ChemistryMicrostructureSample (graphics)Cellular automatonOutcome (probability)Computational MathematicsKey pointMechanics of MaterialsSimulated annealingGeneral Materials ScienceAlgorithmCondensed Matter - Statistical Mechanics
researchProduct