Results 221 to 230 of about 282,414 (265)
A sensitivity study on the measurement of urban polycentricity in chinese cities: Center definition, indicator selection, and their interaction effects. [PDF]
PLoS OneZhu J, Wang Y.
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Multivariate age-related variations in quantitative MRI maps: widespread age-related differences revisited. [PDF]
Front NeurosciMoallemian S +3 more
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An algorithm for non-parametric estimation in state–space models [PDF]
Computational Statistics and Data Analysis, 2021 State-space models are ubiquitous in the statistical literature since they provide a flexible and interpretable framework for analyzing many time series. In most practical applications, the state-space model is specified through a parametric model. However, the specification of such a parametric model may require an important modeling effort or may ...
Pierre Ailliot +2 more
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A non-parametric topical relevance model
Information Retrieval Journal, 2018An information retrieval (IR) system can often fail to retrieve relevant documents due to the incomplete specification of information need in the user’s query. Pseudo-relevance feedback (PRF) aims to improve IR effectiveness by exploiting potentially relevant aspects of the information need present in the documents retrieved in an initial search ...
Debasis Ganguly, Gareth J. F. Jones
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A Non-Parametric Approach to Model Evaluation
Journal of the Operational Research Society, 1986All existing tests and criteria for model evaluation are based on the sum of squared residuals. These measures do not evaluate the performance of a model in predicting turning points in the variable of interest. Here, three tests are proposed to evaluate models on the basis of their ability to predict turning points and to give an unbiased prediction ...
Dadkhah, Kamran M., Zahedi, Fatemeh
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Learning non-parametric models of pronunciation
2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2011As more data becomes available for a given speech recognition task, the natural way to improve recognition accuracy is to train larger models. But, while this strategy yields modest improvements to small systems, the relative gains diminish as the data and models grow.
Brian Hutchinson, Jasha Droppo
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A Bayesian non-parametric stochastic frontier model
Annals of Tourism Research, 2021In this paper, we introduce a new Bayesian non-parametric stochastic frontier (SF) model that addresses the endogeneity problem and relaxes problematic assumptions regarding functional form, and distributional properties. The model can be seen as a competitor to DEA.
Assaf, A. George +3 more
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Non-parametric Model for Background Subtraction
2000Background subtraction is a method typically used to segment moving regions in image sequences taken from a static camera by comparing each new frame to a model of the scene background. We present a novel non-parametric background model and a background subtraction approach. The model can handle situations where the background of the scene is cluttered
Ahmed M. Elgammal +2 more
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Non-parametric identification of generalized Hammerstein models
International Journal of Systems Science, 1998The Hammerstein model is considered in a generalized form, where its nonlinear element can have multi-inputs and a finite memory. The identification of the multi-input finite memory nonimearity and the impulse response sequence of the model is treated using a non-parametric approach. A numerical example is given.
Hosam E. Emara-Shabaik +1 more
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