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Multilevel Weighted Support Vector Machine for Classification on Healthcare Data with Missing Values
TLDR
This work is motivated by the needs of predictive analytics on healthcare data as represented by Electronic Medical Records. Expand
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Polynomial Regression Approaches Using Derivative Information for Uncertainty Quantification
Abstract In this work we describe a polynomial regression approach that uses derivative information for analyzing the performance of a complex system that is described by a mathematical modelExpand
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Proper orthogonal decompositions in multifidelity uncertainty quantification of complex simulation models
TLDR
We investigate uncertainty propagation in the context of high-end complex simulation codes, whose runtime on one configuration is on the order of the total limit of computational resources. Expand
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Fast imbalanced classification of healthcare data with missing values
TLDR
We propose a new multilevel SVM-based method to simultaneously classify large datasets and reduce the effects of missing values. Expand
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ORTHOGONAL BASES FOR POLYNOMIAL REGRESSION WITH DERIVATIVE INFORMATION IN UNCERTAINTY QUANTIFICATION
We discuss the choice of polynomial basis for approximation of uncertainty propagation through complex simulation models with capabilityto outputderivative information.Ourwork ispart of a largerExpand
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Stochastic Finite-Element Approach in Nuclear Reactor Uncertainty Quantification
TLDR
In this work we present a hybrid approach, where the polynomial approximation is computed based on function and derivative information at sample points in the uncertainty region. Expand
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Using Automatic Differentiation in Sensitivity Analysis of Nuclear Simulation Models, invited
TLDR
We introduced a hybrid method that combines sampling techniques with first-order sensitivity analysis to approximate the effects of uncertainty in parameters of a nuclear reactor simulation model. Expand
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Learning of Highly-Filtered Data Manifold Using Spectral Methods
TLDR
We propose a scheme for improving existing tools for recovering and predicting decisions based on singular value decomposition. Expand
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