Search Results - "Pereverzyev, S."

Feed-forward neural networks using cerebral MR spectroscopy and DTI might predict neurodevelopmental outcome in preterm neonates by Janjic, T., Pereverzyev, S., Hammerl, M., Neubauer, V., Lerchner, H., Wallner, V., Steiger, R., Kiechl-Kohlendorfer, U., Zimmermann, M., Buchheim, A., Grams, A. E., Gizewski, E. R.

“…Objectives We aimed to evaluate the ability of feed-forward neural networks (fNNs) to predict the neurodevelopmental outcome (NDO) of very preterm neonates…”
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A meta-learning approach to the regularized learning—Case study: Blood glucose prediction by Naumova, V., Pereverzyev, S.V., Sivananthan, S.

“…In this paper we present a new scheme of a kernel-based regularization learning algorithm, in which the kernel and the regularization parameter are adaptively…”
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PARAMETER CHOICE STRATEGIES FOR LEAST-SQUARES APPROXIMATION OF NOISY SMOOTH FUNCTIONS ON THE SPHERE by PEREVERZYEV, S. V., SLOAN, I. H., TKACHENKO, P.

“…We consider a polynomial reconstruction of smooth functions from their noisy values at discrete nodes on the unit sphere by a variant of the regularized…”
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A Function Approximation Approach to the Prediction of Blood Glucose Levels by Mhaskar, H. N., Pereverzyev, S. V., van der Walt, M. D.

“…The problem of real time prediction of blood glucose (BG) levels based on the readings from a continuous glucose monitoring (CGM) device is a problem of great…”
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Filtered Legendre expansion method for numerical differentiation at the boundary point with application to blood glucose predictions by Mhaskar, Hrushikesh N., Naumova, V., Pereverzyev, S.V.

“…Let f:[-1,1]→R be continuously differentiable. We consider the question of approximating f′(1) from given data of the form (tj,f(tj))j=1M where the points tj…”
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Adaptive Kernel Methods Using the Balancing Principle by De Vito, E., Pereverzyev, S., Rosasco, L.

“…The regularization parameter choice is a fundamental problem in Learning Theory since the performance of most supervised algorithms crucially depends on the…”
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Initial temperature reconstruction for nonlinear heat equation: application to a coupled radiative-conductive heat transfer problem by Pereverzyev, S. S., Pinnau, R., Siedow, N.

“…In a cooling process described by a nonlinear heat equation, we are interested to recover the initial temperature from the temperature measurements that are…”
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A deep learning approach to diabetic blood glucose prediction by Mhaskar, H. N, Pereverzyev, S. V, van der Walt, M. D

“…Front. Appl. Math. Stat., 14 July 2017 We consider the question of 30-minute prediction of blood glucose levels measured by continuous glucose monitoring…”
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Adaptive parameter choice for one-sided finite difference schemes and its application in diabetes technology by Naumova, V., Pereverzyev, S.V., Sivananthan, S.

“…In this paper we discuss the problem of approximation of the first derivative of a function at the endpoint of its definition interval. This problem is…”
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Stenosis Detection in Internal Carotid and Vertebral Arteries With the Use of Diameters Estimated from MRI Data by Nesteruk, Igor, Pereverzyev, Sergiy Jr, Mayer, Lukas, Steiger, Ruth, Kusstatscher, Lukas, Fritscher, Karl, Knoflach, Michael, Gizewski, Elke Ruth

“…Background. Magnetic resonance imaging (MRI) offers the opportunity to quantify the vessel diameters in vivo. This technique can have a breakthrough impact on…”
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A function approximation approach to the prediction of blood glucose levels by Mhaskar, H. N, Pereverzyev, S. V, van der Walt, M. D

“…The problem of real time prediction of blood glucose (BG) levels based on the readings from a continuous glucose monitoring (CGM) device is a problem of great…”
Get full text