Search results for "abstract"

showing 10 items of 1959 documents

The arithmetic decomposition of central Cantor sets

2018

Abstract Every central Cantor set of positive Lebesgue measure is the arithmetic sum of two central Cantor sets of Lebesgue measure zero. Under some mild condition this result can be strengthened by stating that the summands can be chosen to be C s regular if the initial set is of this class.

Class (set theory)Mathematics::Dynamical SystemsLebesgue measureApplied Mathematics010102 general mathematicsZero (complex analysis)Analysi02 engineering and technology01 natural sciencesCentral Cantor setCantor setCombinatoricsSet (abstract data type)Arithmetic progression0202 electrical engineering electronic engineering information engineeringDecomposition (computer science)Palis hypothesiArithmetic decomposition020201 artificial intelligence & image processing0101 mathematicsComputer Science::DatabasesAnalysisMathematicsJournal of Mathematical Analysis and Applications
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Learning Molecular Classes from Small Numbers of Positive Examples Using Graph Grammars

2021

We consider the following problem: A researcher identified a small number of molecules with a certain property of interest and now wants to find further molecules sharing this property in a database. This can be described as learning molecular classes from small numbers of positive examples. In this work, we propose a method that is based on learning a graph grammar for the molecular class. We consider the type of graph grammars proposed by Althaus et al. [2], as it can be easily interpreted and allows relatively efficient queries. We identify rules that are frequently encountered in the positive examples and use these to construct a graph grammar. We then classify a molecule as being conta…

Class (set theory)Property (philosophy)Theoretical computer scienceGrammarRule-based machine translationComputer scienceSmall numbermedia_common.quotation_subjectGraph (abstract data type)Construct (python library)Type (model theory)media_common
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The linearized Calderón problem on complex manifolds

2019

International audience; In this note we show that on any compact subdomain of a Kähler manifold that admits sufficiently many global holomorphic functions , the products of harmonic functions form a complete set. This gives a positive answer to the linearized anisotropic Calderón problem on a class of complex manifolds that includes compact subdomains of Stein manifolds and sufficiently small subdomains of Kähler manifolds. Some of these manifolds do not admit limiting Carleman weights, and thus cannot by treated by standard methods for the Calderón problem in higher dimensions. The argument is based on constructing Morse holo-morphic functions with approximately prescribed critical points.…

Class (set theory)Pure mathematicsGeneral MathematicsHolomorphic function01 natural sciencesinversio-ongelmatSet (abstract data type)symbols.namesake[MATH.MATH-AP]Mathematics [math]/Analysis of PDEs [math.AP]0101 mathematics[MATH]Mathematics [math]complex manifoldMathematics::Symplectic GeometryMathematicsosittaisdifferentiaaliyhtälötCalderón problemMathematics::Complex VariablesApplied MathematicsRiemann surface010102 general mathematicsLimitingStandard methodsManifold010101 applied mathematicsHarmonic function[MATH.MATH-DG]Mathematics [math]/Differential Geometry [math.DG]symbolsinverse problemMathematics::Differential Geometrymonistot
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Pattern classification using a new border identification paradigm: The nearest border technique

2015

Abstract There are many paradigms for pattern classification such as the optimal Bayesian, kernel-based methods, inter-class border identification schemes, nearest neighbor methods, nearest centroid methods, among others. As opposed to these, this paper pioneers a new paradigm, which we shall refer to as the nearest border (NB) paradigm. The philosophy for developing such a NB strategy is as follows: given the training data set for each class, we shall attempt to create borders for each individual class. However, unlike the traditional border identification (BI) methods, we do not undertake this by using inter-class criteria; rather, we attempt to obtain the border for a specific class in t…

Class (set theory)Theoretical computer scienceComputer sciencebusiness.industryCognitive NeuroscienceCentroidComputer Science Applicationsk-nearest neighbors algorithmSet (abstract data type)Kernel (linear algebra)Identification (information)Artificial IntelligenceKernel (statistics)OutlierArtificial intelligencebusiness
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TOPOLOGICAL QUANTUM DOUBLE

1994

Following a preceding paper showing how the introduction of a t.v.s. topology on quantum groups led to a remarkable unification and rigidification of the different definitions, we adapt here, in the same way, the definition of quantum double. This topological double is dualizable and reflexive (even for infinite dimensional algebras). In a simple case we show, considering the double as the "zero class" of an extension theory, the uniqueness of the double structure as a quasi-Hopf algebra. A la suite d'un précédent article montrant comment l'introduction d'une topologie d'e.v.t. sur les groupes quantiques permet une unification et une rigidification remarquables des différentes définitions,…

Class (set theory)UnificationSimple (abstract algebra)Zero (complex analysis)Structure (category theory)Statistical and Nonlinear PhysicsUniquenessExtension theoryTopologyQuantumMathematical PhysicsMathematicsReviews in Mathematical Physics
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Comparative analysis of architectures for monitoring cloud computing infrastructures

2015

The lack of control over the cloud resources is one of the main disadvantages associated to cloud computing. The design of efficient architectures for monitoring such resources can help to overcome this problem. This contribution describes a complete set of architectures for monitoring cloud computing infrastructures, and provides a taxonomy of them. The architectures are described in detail, compared among them, and analysed in terms of performance, scalability, usage of resources, and security capabilities. The architectures have been implemented in real world settings and empirically validated against a real cloud computing infrastructure based on OpenStack. More than 1000 virtual machin…

Cloud computing securityComputer Networks and Communicationsbusiness.industryComputer scienceDistributed computingCloud computingcomputer.software_genreSet (abstract data type)Utility computingHardware and ArchitectureVirtual machineScalabilitybusinesscomputerSoftwareFuture Generation Computer Systems
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Scaling Up a Metric Learning Algorithm for Image Recognition and Representation

2008

Maximally Collapsing Metric Learning is a recently proposed algorithm to estimate a metric matrix from labelled data. The purpose of this work is to extend this approach by considering a set of landmark points which can in principle reduce the cost per iteration in one order of magnitude. The proposal is in fact a generalized version of the original algorithm that can be applied to larger amounts of higher dimensional data. Exhaustive experimentation shows that very similar behavior at a lower cost is obtained for a wide range of the number of landmark points used.

Clustering high-dimensional dataSet (abstract data type)Range (mathematics)LandmarkMetric (mathematics)Landmark pointRepresentation (mathematics)AlgorithmFacial recognition systemMathematics
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Regularized Regression Incorporating Network Information: Simultaneous Estimation of Covariate Coefficients and Connection Signs

2014

We develop an algorithm that incorporates network information into regression settings. It simultaneously estimates the covariate coefficients and the signs of the network connections (i.e. whether the connections are of an activating or of a repressing type). For the coefficient estimation steps an additional penalty is set on top of the lasso penalty, similarly to Li and Li (2008). We develop a fast implementation for the new method based on coordinate descent. Furthermore, we show how the new methods can be applied to time-to-event data. The new method yields good results in simulation studies concerning sensitivity and specificity of non-zero covariate coefficients, estimation of networ…

Clustering high-dimensional databusiness.industryjel:C41jel:C13Machine learningcomputer.software_genreRegressionhigh-dimensional data gene expression data pathway information penalized regressionConnection (mathematics)Set (abstract data type)Lasso (statistics)CovariateArtificial intelligenceSensitivity (control systems)businessCoordinate descentAlgorithmcomputerMathematics
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Receptive Reason: Alexander of Aphrodisias on Material Intellect

2010

AbstractAccording to Alexander of Aphrodisias, our potential intellect is a purely receptive capacity. Alexander also claims that, in order for us to actualise our intellectual potentiality, the intellect needs to abstract what is intelligible from enmattered perceptible objects. Now a problem emerges: How is it possible for a purely receptive capacity to perform such an abstraction? It will be argued that even though Alexander’s reaction to this question causes some tension in his theory, the philosophical motivation for it is a sound one. Rather than a calculation of actualities and potentialities, the doctrine of receptivity is supposed to explain how human beings come to grasp universal…

Cognitive sciencePhilosophyHistoryHistory and Philosophy of ScienceAncient philosophyPhilosophymedia_common.quotation_subjectDoctrineIntellectOrder (virtue)EpistemologyAbstraction (mathematics)media_commonPhronesis
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Imitation Learning and Anchoring through Conceptual Spaces

2007

In order to have a robotic system able to effectively learn by imitation and not merely reproduce the movements of a human teacher, the system should have the capability to deeply understand the perceived actions to be imitated. This paper deals with the development of a cognitive architecture for learning by imitation in which a rich conceptual representation of the observed actions is built. The purpose of the following discussion is to show how the same conceptual representation can be used both in a bottom-up approach, in order to learn sequences of actions by imitation learning paradigm, and in a top-down approach, in order to anchor the symbolical representations to the perceptual act…

Cognitive scienceSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniComputer sciencebusiness.industrymedia_common.quotation_subjectRepresentation (systemics)AnchoringCognitive architectureHUMAN ARM MOVEMENTS; SYSTEM; TIMERobotics Imitation LearningArtificial IntelligenceSimple (abstract algebra)Order (business)PerceptionArtificial intelligenceCognitive imitationImitationbusinessmedia_common
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