Search results for "artificial intelligence"

showing 10 items of 6122 documents

LeSSS: Learned Shared Semantic Spaces for Relating Multi-Modal Representations of 3D Shapes

2015

In this paper, we propose a new method for structuring multi-modal representations of shapes according to semantic relations. We learn a metric that links semantically similar objects represented in different modalities. First, 3D-shapes are associated with textual labels by learning how textual attributes are related to the observed geometry. Correlations between similar labels are captured by simultaneously embedding labels and shape descriptors into a common latent space in which an inner product corresponds to similarity. The mapping is learned robustly by optimizing a rank-based loss function under a sparseness prior for the spectrum of the matrix of all classifiers. Second, we extend …

Theoretical computer sciencebusiness.industryComputer scienceRank (computer programming)Cognitive neuroscience of visual object recognitioncomputer.software_genreComputer Graphics and Computer-Aided DesignProduct (mathematics)Similarity (psychology)Line (geometry)Metric (mathematics)Collaborative filteringEmbeddingArtificial intelligencebusinesscomputerNatural language processingComputer Graphics Forum
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Learning small programs with additional information

1997

This paper was inspired by [FBW 94]. An arbitrary upper bound on the size of some program for the target function suffices for the learning of some program for this function. In [FBW 94] it was discovered that if “learning” is understood as “identification in the limit,” then in some programming languages it is possible to learn a program of size not exceeding the bound, while in some other programming languages this is not possible.

Theoretical computer sciencebusiness.industryComputer sciencemedia_common.quotation_subjectInductive reasoningMachine learningcomputer.software_genreUpper and lower boundsIdentification (information)Recursive functionsArtificial intelligenceLimit (mathematics)businessFunction (engineering)computermedia_common
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On the use of neighbourhood-based non-parametric classifiers

1997

Alternative non-parametric classification schemes, which come from the use of different definitions of neighbourhood, are introduced. In particular, the Nearest Centroid Neighbourhood along with the neighbourhood relation derived from the Gabriel Graph and the Relative Neighbourhood Graph are used to define the corresponding (k-)Nearest Neighbour-like classifiers. Experimental results are reported to compare the performance of the approaches proposed here to the one obtained with the k-Nearest Neighbours rule.

Theoretical computer sciencebusiness.industryGabriel graphNonparametric statisticsCentroidPattern recognitionClassification schemeNeighbourhood graphComputingMethodologies_PATTERNRECOGNITIONNeighbourhood components analysisArtificial IntelligenceSignal ProcessingNeighbourhood systemComputingMethodologies_GENERALComputer Vision and Pattern RecognitionArtificial intelligencebusinessNeighbourhood (mathematics)SoftwareMathematics
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The power of procrastination in inductive inference: How it depends on used ordinal notations

1995

We consider inductive inference with procrastination. Usually it is defined using constructive ordinals. For constructive ordinals there exist many different systems of notations. In this paper we study how the power of inductive inference depends on used system of notations.

Theoretical computer sciencebusiness.industrymedia_common.quotation_subjectProcrastinationInductive reasoningMachine learningcomputer.software_genreNotationConstructivePower (physics)Mathematics::LogicArtificial intelligencebusinesscomputermedia_commonMathematics
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An ontological-based knowledge organization for bioinformatics workflow management system

2012

Motivation and Objectives In the field of Computer Science, ontologies represent formal structures to define and organize knowledge of a specific application domain (Chandrasekaran et al., 1999). An ontology is composed of entities, called classes, and relationships among them. Classes are characterized by features, called attributes, and they can be arranged into a hierarchical organization. Ontologies are a fundamental instrument in Artificial Intelligence for the development of Knowledge-Based Systems (KBS). With its formal and well defined structure, in fact, an ontology provides a machine-understandable language that allows automatic reasoning for problems resolution. Typical KBS are E…

Theoretical computer scienceworkflow management systembusiness.industryComputer scienceIntelligent decision support systemBioinformatics workflow management systembioinformaticsOntology (information science)Solvercomputer.software_genreExpert systemWorkflowArtificial intelligenceontologybusinessCluster analysiscomputerWorkflow management system
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The computational power of continuous time neural networks

1997

We investigate the computational power of continuous-time neural networks with Hopfield-type units. We prove that polynomial-size networks with saturated-linear response functions are at least as powerful as polynomially space-bounded Turing machines.

TheoryofComputation_COMPUTATIONBYABSTRACTDEVICESQuantitative Biology::Neurons and CognitionComputational complexity theoryArtificial neural networkComputer sciencebusiness.industryComputer Science::Neural and Evolutionary ComputationNSPACEComputational resourcePower (physics)Turing machinesymbols.namesakeCellular neural networksymbolsArtificial intelligenceTypes of artificial neural networksbusiness
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A Logic of Discovery

1998

A logic of discovery is introduced. In this logic, true sentences are discovered over time based on arriving data. A notion of expectation is introduced to reflect the growing certainty that a universally quantified sentence is true as more true instances are observed. The logic is shown to be consistent and complete. Monadic predicates are considered as a special case

TheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGESTheoretical computer scienceComputer sciencebusiness.industrymedia_common.quotation_subjectArtificial intelligenceSpecial caseCertaintyMonad (functional programming)businessPredicate (grammar)Sentencemedia_common
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Properties and constraints of cheating-immune secret sharing schemes

2006

AbstractA secret sharing scheme is a cryptographic protocol by means of which a dealer shares a secret among a set of participants in such a way that it can be subsequently reconstructed by certain qualified subsets. The setting we consider is the following: in a first phase, the dealer gives in a secure way a piece of information, called a share, to each participant. Then, participants belonging to a qualified subset send in a secure way their shares to a trusted party, referred to as a combiner, who computes the secret and sends it back to the participants.Cheating-immune secret sharing schemes are secret sharing schemes in the above setting where dishonest participants, during the recons…

TheoryofComputation_MISCELLANEOUSHomomorphic secret sharingCryptography0102 computer and information sciences02 engineering and technologyShared secretComputer securitycomputer.software_genre01 natural sciencesSecret sharingCheating0202 electrical engineering electronic engineering information engineeringDiscrete Mathematics and CombinatoricsSecret sharingMathematicsbusiness.industryApplied MathematicsCryptographic protocol16. Peace & justiceShamir's Secret Sharing010201 computation theory & mathematicsResilient functionsCryptographySecure multi-party computation020201 artificial intelligence & image processingVerifiable secret sharingbusinesscomputerDiscrete Applied Mathematics
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Constructivismo, psicoterapias cognitivas de reestructuración y enfoques contextuales

2020

En este trabajo se establecen las diferencias y convergencias principales entre los modelos cognitivos de reestructuración, los constructivistas y los contextuales. Partiendo de una breve revisión histórica se podrá enmarcar el surgimiento de cada uno de estos enfoques e, igualmente, las diferencias epistemológicas y ontológicas entre ellos. Estos modelos se analizan, principalmente, haciendo hincapié en sus conceptos principales y en las técnicas desarrolladas que, en principio, serían coherentes con su marco teórico. Igualmente, la coherencia entre teoría y práctica se hace evidente mediante el desarrollo de un tipo concreto, y diferente, de relación terapéutica en cada modelo. La conclus…

Therapeutic relationshipField (Bourdieu)Cognitive restructuringPerspective (graphical)General Earth and Planetary SciencesFrame (artificial intelligence)SociologyCoherence (linguistics)General Environmental ScienceEpistemologyRevista de Psicoterapia
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A novel dynamic multi-model relevance feedback procedure for content-based image retrieval

2016

This paper deals with the problem of image retrieval in large databases with a big semantic gap by a relevance feedback procedure. We present a novel algorithm for modelling the users's preferences in the content-based image retrieval system.The proposed algorithm considers the probability of an image belonging to the set of those sought by the user, and estimates the parameters of several local logistic regression models whose inputs are the low-level image features. A Principal Component Analysis method is applied to the original vector to reduce its high dimensionality. The relevance probabilities predicted by these local models are combined by means of a weighted average. These weights …

Thesaurus (information retrieval)Computer scienceCognitive NeuroscienceRelevance feedback020207 software engineering02 engineering and technologycomputer.software_genreContent-based image retrievalComputer Science ApplicationsSet (abstract data type)Search engineArtificial IntelligenceFeature (computer vision)Principal component analysis0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingRelevance (information retrieval)Data miningcomputerImage retrievalSemantic gapNeurocomputing
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