Search results for "FOS: Computer and information sciences"

showing 7 items of 857 documents

The Syllogistic with Unity

2011

We extend the language of the classical syllogisms with the sentence-forms “At most 1 p is a q” and “More than 1 p is a q”. We show that the resulting logic does not admit a finite set of syllogism-like rules whose associated derivation relation is sound and complete, even when reductio ad absurdum is allowed.

logic and natural languageFOS: Computer and information sciencesPure mathematicsComputer Science - Logic in Computer Sciencecomputational complexityComputational complexity theoryComputational logicSyllogismMathematics - Logicproof theorysyllogismsDerivation relationLogic in Computer Science (cs.LO)Reductio ad absurdumPhilosophyPhilosophy of logicProof theoryCalculusFOS: MathematicsF.4.0Logic (math.LO)Finite setMathematics03B65
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Bayesian semiparametric long memory models for discretized event data

2020

We introduce a new class of semiparametric latent variable models for long memory discretized event data. The proposed methodology is motivated by a study of bird vocalizations in the Amazon rain forest; the timings of vocalizations exhibit self-similarity and long range dependence. This rules out Poisson process based models where the rate function itself is not long range dependent. The proposed class of FRActional Probit (FRAP) models is based on thresholding, a latent process. This latent process is modeled by a smooth Gaussian process and a fractional Brownian motion by assuming an additive structure. We develop a Bayesian approach to inference using Markov chain Monte Carlo and show g…

mallintaminenFOS: Computer and information sciencesStatistics and Probabilitylong range dependenceaikasarjatMarkovin ketjutfractional Brownian motionsademetsätekologinen mallinnusStatistics - ApplicationsArticleMethodology (stat.ME)fractalApplications (stat.AP)AmazonStatistics - Methodologylatent Gaussian process modelstodennäköisyyslaskentanonparametric Bayesbayesilainen menetelmägaussiset prosessitmatemaattinen tilastotiedeluonnonäänetlinnut -- äänetluonnon monimuotoisuusMonte Carlo -menetelmätComputer Science::SoundModeling and Simulationprobitfraktaalittime seriesStatistics Probability and UncertaintyThe Annals of Applied Statistics
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Very narrow quantum OBDDs and width hierarchies for classical OBDDs

2014

In the paper we investigate a model for computing of Boolean functions - Ordered Binary Decision Diagrams (OBDDs), which is a restricted version of Branching Programs. We present several results on the comparative complexity for several variants of OBDD models. - We present some results on the comparative complexity of classical and quantum OBDDs. We consider a partial function depending on a parameter k such that for any k > 0 this function is computed by an exact quantum OBDD of width 2, but any classical OBDD (deterministic or stable bounded-error probabilistic) needs width 2 k+1. - We consider quantum and classical nondeterminism. We show that quantum nondeterminism can be more efficien…

nondeterminismFOS: Computer and information sciencespartial functionsGeneral Mathematicsquantum computation010102 general mathematics0102 computer and information sciencesOBDDComputational Complexity (cs.CC)Computer Science::Artificial IntelligenceComputer Science::Computational Complexity01 natural scienceswidth hierarchyComputer Science - Computational Complexity010201 computation theory & mathematicsComputer Science::Logic in Computer Science0101 mathematics
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Prioritizing covariates in the planning of future studies in the meta-analytic framework

2016

Science can be seen as a sequential process where each new study augments evidence to the existing knowledge. To have the best prospects to make an impact in this process, a new study should be designed optimally taking into account the previous studies and other prior information. We propose a formal approach for the covariate prioritization, i.e., the decision about the covariates to be measured in a new study. The decision criteria can be based on conditional power, change of the p-value, change in lower confidence limit, Kullback-Leibler divergence, Bayes factors, Bayesian false discovery rate or difference between prior and posterior expectation. The criteria can be also used for decis…

powerMethodology (stat.ME)FOS: Computer and information sciencesdesignmeta-analyysiscientific methodnäyttöön perustuva lääketiedeStatistics - Methodology
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Enhancing identification of causal effects by pruning

2018

Causal models communicate our assumptions about causes and effects in real-world phe- nomena. Often the interest lies in the identification of the effect of an action which means deriving an expression from the observed probability distribution for the interventional distribution resulting from the action. In many cases an identifiability algorithm may return a complicated expression that contains variables that are in fact unnecessary. In practice this can lead to additional computational burden and increased bias or inefficiency of estimates when dealing with measurement error or missing data. We present graphical criteria to detect variables which are redundant in identifying causal effe…

päättelyFOS: Computer and information sciencesalgorithmcausal modelMachine Learning (stat.ML)Machine Learning (cs.LG)Computer Science - Learningleikkaus (kasvit)koneoppiminenStatistics - Machine Learningidentiafiabilityalgoritmitkausaliteetticausal inferencetunnistaminen
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A Completeness Proof for a Regular Predicate Logic with Undefined Truth Value

2023

We provide a sound and complete proof system for an extension of Kleene's ternary logic to predicates. The concept of theory is extended with, for each function symbol, a formula that specifies when the function is defined. The notion of "is defined" is extended to terms and formulas via a straightforward recursive algorithm. The "is defined" formulas are constructed so that they themselves are always defined. The completeness proof relies on the Henkin construction. For each formula, precisely one of the formula, its negation, and the negation of its "is defined" formula is true on the constructed model. Many other ternary logics in the literature can be reduced to ours. Partial functions …

ternary logicFOS: Computer and information sciencesComputer Science - Logic in Computer ScienceTheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGESpartial functionscompletenessLogicFOS: Mathematics03B50 03F03 (Primary) 03B10 (Secondary)predikaattilogiikkaMathematics - LogicLogic (math.LO)Logic in Computer Science (cs.LO)Notre Dame Journal of Formal Logic
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AI Ethics in Industry: A Research Framework

2019

Artificial Intelligence (AI) systems exert a growing influence on our society. As they become more ubiquitous, their potential negative impacts also become evident through various real-world incidents. Following such early incidents, academic and public discussion on AI ethics has highlighted the need for implementing ethics in AI system development. However, little currently exists in the way of frameworks for understanding the practical implementation of AI ethics. In this paper, we discuss a research framework for implementing AI ethics in industrial settings. The framework presents a starting point for empirical studies into AI ethics but is still being developed further based on its pr…

transparencyFOS: Computer and information sciencesAI developmentComputingMilieux_THECOMPUTINGPROFESSIONresearch frameworkvastuullisuustekoälyartificial intelligenceGeneralLiterature_MISCELLANEOUSComputer Science - Computers and SocietyAI ethicsComputingMethodologies_PATTERNRECOGNITIONaccountabilityComputers and Society (cs.CY)responsibilityetiikkateollisuus
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