Results 31 to 40 of about 8,187,354 (351)
Sensitivity estimates from characteristic functions [PDF]
2007 Winter Simulation Conference, 2007 The likelihood ratio method (LRM) is a technique for estimating derivatives of expectations through simulation. LRM estimators are constructed from the derivatives of probability densities of inputs to a simulation. We investigate the application of the likelihood ratio method for sensitivity estimation when the relevant densities for the underlying ...
Paul Glasserman, Zongjian Liu
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Sensitivity estimation of conditional value at risk using randomized quasi-Monte Carlo [PDF]
European Journal of Operational Research, 2019 Conditional value at risk (CVaR) is a popular measure for quantifying portfolio risk. Sensitivity analysis of CVaR is very useful in risk management and gradient-based optimization algorithms.
Zhijian He
semanticscholar +1 more source
Sensitivity analysis and parameter estimation for distributed hydrological modeling: potential of variational methods [PDF]
, 2009 Variational methods are widely used for the analysis and control of computationally intensive spatially distributed systems. In particular, the adjoint state method enables a very efficient calculation of the derivatives of an objective function ...
Dartus, Denis +8 more
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Viscosity and effusion rate identification from free surface data
International Journal of Thermofluids, 2022 Based on new explicit expressions for sensitivity coefficients, this study proposes a new method to solve two inverse problems in time-dependent three-dimensional gravity-driven thin film flow down an inclined plane governed by free-surface lubrication ...
Farzad Mohebbi, Mathieu Sellier
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Quantum Risk-Sensitive Estimation and Robustness [PDF]
IEEE Transactions on Automatic Control, 2009 This paper studies a quantum risk-sensitive estimation problem and investigates robustness properties of the filter. This is a direct extension to the quantum case of analogous classical results. All investigations are based on a discrete approximation model of the quantum system under consideration.
Naoki Yamamoto, Luc Bouten
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Rectified Softmax Loss With All-Sided Cost Sensitivity for Age Estimation
IEEE Access, 2020 In Convolutional Neural Network (ConvNet) based age estimation algorithms, softmax loss is usually chosen as the loss function directly, and the problems of Cost Sensitivity (CS), such as class imbalance and misclassification cost difference between ...
Daxiang Li +3 more
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Double Kernel Estimation of Sensitivities [PDF]
Journal of Applied Probability, 2009 In this paper we address the general issue of estimating the sensitivity of the expectation of a random variable with respect to a parameter characterizing its evolution. In finance, for example, the sensitivities of the price of a contingent claim are called the Greeks. A new way of estimating the Greeks has recently been introduced in Elie, Fermanian
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Sensitivity estimation for personal interview survey questions
Statistica, 2007 This paper proposes an optional RRT method to estimate the sensitivity level of personal interview survey questions with quantitative response. The method is similar to the one used by Gupta et al. (2002) but estimates both the average response level and
Sat Gupta, Javid Shabbir
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Reference data set for camera spectral sensitivity estimation. [PDF]
Journal of The Optical Society of America A-optics Image Science and Vision, 2015 In this article, we describe a spectral sensitivity measurement procedure at the National Physical Laboratory, London, with the aim of obtaining ground truth spectral sensitivity functions for Nikon D5100 and Sigma SD1 Merill cameras.
Maryam M. Darrodi +3 more
semanticscholar +2 more sources
Energies, 2021 This paper presents a numerical method to address function estimation problems in inverse heat transfer problems using parameter estimation approach without prior information on the functional form of the variable to be estimated.
Farzad Mohebbi, Mathieu Sellier
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