Results 11 to 20 of about 4,214,964 (288)
Data-driven assessment of eQTL mapping methods [PDF]
BMC Genomics, 2010 Background The analysis of expression quantitative trait loci (eQTL) is a potentially powerful way to detect transcriptional regulatory relationships at the genomic scale.
Schughart Klaus +3 more
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On the Data-Driven COS Method [PDF]
SSRN Electronic Journal, 2017 In this paper, we present the data-driven COS method, ddCOS. It is a Fourier-based financial option valuation method which assumes the availability of asset data samples: a characteristic function of the underlying asset probability density function is not required.
Álvaro Leitao +3 more
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A Data Driven Method for Computing Quasipotentials
CoRR, 2020 The quasipotential is a natural generalization of the concept of energy functions to non-equilibrium systems. In the analysis of rare events in stochastic dynamics, it plays a central role in characterizing the statistics of transition events and the likely transition paths.
Bo Lin, Qianxiao Li, Weiqing Ren
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Data‐driven execution of fast multipole methods [PDF]
Concurrency and Computation: Practice and Experience, 2013 SUMMARYFast multipole methods (FMMs) havecomplexity, are compute bound, and require very little synchronization, which makes them a favorable algorithm on next‐generation supercomputers. Their most common application is to accelerateN‐body problems, but they can also be used to solve boundary integral equations.
Hatem Ltaief, Rio Yokota
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Experimental comparison of parameter estimation methods in adaptive robot control [PDF]
, 1995 In the literature on adaptive robot control a large variety of parameter estimation methods have been proposed, ranging from tracking-error-driven gradient methods to combined tracking- and prediction-error-driven least-squares type adaptation methods ...
Berghuis, Harry +2 more
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Estimator selection: a new method with applications to kernel density estimation [PDF]
, 2016 Estimator selection has become a crucial issue in non parametric estimation. Two widely used methods are penalized empirical risk minimization (such as penalized log-likelihood estimation) or pairwise comparison (such as Lepski's method). Our aim in this
Lacour, Claire +2 more
core +5 more sources
Application of Data Driven Methods for Condition Monitoring Maintenance
Chemical Engineering Transactions, 2013 Nowadays, there is an increasing demand for Condition Based Maintenance (CBM) activities as time-directed maintenance are observed to be inefficient in many situations.
I. Marton +3 more
doaj +1 more source
Multidimensional approximation of nonlinear dynamical systems [PDF]
, 2019 A key task in the field of modeling and analyzing nonlinear dynamical systems is the recovery of unknown governing equations from measurement data only.
Eisert, Jens +3 more
core +2 more sources
International Journal of Prognostics and Health Management, 2016 In the 2015 PHM Data Challenge Competition, the goal of the competition problem was to diagnose failure of industrial plant systems using incomplete data. The available data consisted of sensor measurements, control reference signals, and fault logs.
Hyunjae Kim +7 more
doaj +1 more source
Data-Driven Machine-Learning Methods for Diabetes Risk Prediction
Sensors, 2022 Diabetes mellitus is a chronic condition characterized by a disturbance in the metabolism of carbohydrates, fats and proteins. The most characteristic disorder in all forms of diabetes is hyperglycemia, i.e., elevated blood sugar levels.
Elias Dritsas, Maria Trigka
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